Department of Engineering

Prof. Zoubin Ghahramani - Publications

Number of items: 452.

Article

Kimura, A and Ghahramani, Z and Takeuchi, K and Iwata, T and Ueda, N (2019) Few-shot learning of neural networks from scratch by pseudo example optimization. British Machine Vision Conference 2018, BMVC 2018.

Penfold, CA and Sybirna, A and Reid, JE and Huang, Y and Wernisch, L and Ghahramani, Z and Grant, M and Surani, MA (2018) Branch-recombinant Gaussian processes for analysis of perturbations in biological time series. Bioinformatics, 34. i1005-i1013. ISSN 1367-4803

Ścibior, AM and Kammar, O and Ghahramani, Z (2018) Functional Programming for Modular Bayesian Inference. Proceedings of the ACM on Programming Languages, 2. pp. 1-29.

Hron, J and De G Matthews, AG and Ghahramani, Z (2018) Variational Bayesian dropout: Pitfalls and fixes. 35th International Conference on Machine Learning, ICML 2018, 5. pp. 3199-3219.

Mukuta, Y and Kimura, A and Adrian, DB and Ghahramani, Z (2018) Weakly supervised collective feature learning from curated media. 32nd AAAI Conference on Artificial Intelligence, AAAI 2018. pp. 7260-7267.

Matthews, AGDG and Van Der Wilk, M and Nickson, T and Fujii, K and Boukouvalas, A and León-Villagrá, P and Ghahramani, Z and Hensman, J (2017) GPflow: A Gaussian Process Library using TensorFlow. Journal of Machine Learning Research, 18. ISSN 1532-4435

Lee, J and Heaukulani, C and Ghahramani, Z and James, LF and Choi, S (2017) Bayesian inference on random simple graphs with power law degree distributions. 34th International Conference on Machine Learning, ICML 2017, 4. pp. 3153-3168.

Tripuraneni, N and Rowland, M and Ghahramani, Z and Turner, R (2017) Magnetic hamiltonian Monte Carlo. 34th International Conference on Machine Learning, ICML 2017, 7. pp. 5292-5312.

Hernández-Lobato, JM and Gelbart, MA and Adams, RP and Hoffman, MW and Ghahramani, Z (2016) A General Framework for Constrained Bayesian Optimization using Information-based Search. Journal of Machine Learning Research, 17.

Nazabal, A and Garcia-Moreno, P and Artes-Rodriguez, A and Ghahramani, Z (2016) Human Activity Recognition by Combining a Small Number of Classifiers. IEEE Journal of Biomedical and Health Informatics, 20. pp. 1342-1351. ISSN 2168-2194

Balog, M and Lakshminarayanan, B and Ghahramani, Z and Roy, DM and Teh, YW (2016) The Mondrian Kernel. 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016). pp. 32-41.

Iwata, T and Lloyd, JR and Ghahramani, Z (2016) Unsupervised Many-to-Many Object Matching for Relational Data. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38. pp. 607-617. ISSN 0162-8828

Frellsen, J and Winther, O and Ghahramani, Z and Ferkinghoff-Borg, J (2016) Bayesian generalised ensemble Markov chain Monte Carlo. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, AISTATS 2016, 51. pp. 408-416.

Gal, Y and Ghahramani, Z (2016) Dropout as a Bayesian Approximation: Appendix. 33rd International Conference on Machine Learning, ICML 2016, 3. pp. 1661-1680.

Gal, Y and Ghahramani, Z (2016) Dropout as a Bayesian approximation: Representing model uncertainty in deep learning. 33rd International Conference on Machine Learning, ICML 2016, 3. pp. 1651-1660.

Alexander, AG and Hensman, J and Turner, RE and Ghahramani, Z (2016) On sparse variational methods and the Kullback-Leibler divergence between stochastic processes. Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, AISTATS 2016. pp. 231-239.

Chen, Y and Ghahramani, Z (2016) Scalable discrete sampling as a multi-armed bandit problem. 33rd International Conference on Machine Learning, ICML 2016, 5. pp. 3691-3707.

Gal, Y and Ghahramani, Z (2016) A theoretically grounded application of dropout in recurrent neural networks. Advances in Neural Information Processing Systems. pp. 1027-1035. ISSN 1049-5258

Bousmalis, K and Zafeiriou, S and Morency, LP and Pantic, M and Ghahramani, Z (2015) Variational infinite hidden conditional random fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37. pp. 1917-1929. ISSN 0162-8828

Bratières, S and Quadrianto, N and Ghahramani, Z (2015) GPstruct: Bayesian Structured Prediction Using Gaussian Processes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37. pp. 1514-1520. ISSN 0162-8828

Shah, A and Knowles, DA and Ghahramani, Z (2015) An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process.

Quadrianto, N and Ghahramani, Z (2015) A very simple safe-Bayesian random forest. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37. pp. 1297-1303. ISSN 0162-8828

Ghahramani, Z (2015) Probabilistic machine learning and artificial intelligence. Nature, 521. pp. 452-459. ISSN 0028-0836

Dziugaite, GK and Roy, DM and Ghahramani, Z (2015) Training generative neural networks via Maximum Mean Discrepancy optimization.

Wade, S and Ghahramani, Z (2015) Bayesian cluster analysis: Point estimation and credible balls.

Knowles, DA and Ghahramani, Z (2015) Pitman yor diffusion trees for bayesian hierarchical clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37. pp. 271-289. ISSN 0162-8828

Palla, K and Knowles, DA and Ghahramani, Z (2015) Relational learning and network modelling using infinite latent attribute models. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37. pp. 462-474. ISSN 0162-8828

Cunningham, JP and Ghahramani, Z (2015) Linear dimensionality reduction: Survey, insights, and generalizations. Journal of Machine Learning Research, 16. pp. 2859-2900. ISSN 1532-4435

Cunningham, JP and Ghahramani, Z (2015) Linear Dimensionality Reduction: Survey, Insights, and Generalizations. JOURNAL OF MACHINE LEARNING RESEARCH, 16. pp. 2859-2900. ISSN 1532-4435

Tarran, B and Ghahramani, Z (2015) How machines learned to think statistically. Significance, 12. pp. 8-15. ISSN 1740-9705

Gal, Y and Chen, Y and Ghahramani, Z (2015) Latent Gaussian processes for distribution estimation of multivariate categorical data. 32nd International Conference on Machine Learning, ICML 2015, 1. pp. 645-654.

Hensman, J and De Matthews, AG and Filippone, M and Ghahramani, Z (2015) MCMC for variationally sparse Gaussian processes. Advances in Neural Information Processing Systems, 2015-J. pp. 1648-1656. ISSN 1049-5258

Gu, S and Ghahramani, Z and Turner, RE (2015) Neural adaptive sequential Monte Carlo. Advances in Neural Information Processing Systems, 2015-J. pp. 2629-2637. ISSN 1049-5258

Shah, A and Ghahramani, Z (2015) Parallel predictive entropy search for batch global optimization of expensive objective functions. Advances in Neural Information Processing Systems, 2015-J. pp. 3330-3338. ISSN 1049-5258

Hernández-Lobato, JM and Gelbart, MA and Hoffman, MW and Adams, RP and Ghahramani, Z (2015) Predictive Entropy Search for Bayesian optimization with unknown constraints. 32nd International Conference on Machine Learning, ICML 2015, 2. pp. 1699-1707.

Hensman, J and Matthews, AG and Ghahramani, Z (2015) Scalable variational Gaussian process classification. Journal of Machine Learning Research, 38. pp. 351-360. ISSN 1532-4435

Lloyd, JR and Duvenaud, D and Grosse, R and Tenenbaum, JB and Ghahramani, Z (2014) Automatic construction and natural-language description of nonparametric regression models. Proceedings of the National Conference on Artificial Intelligence, 2. pp. 1242-1250.

Duvenaud, D and Rippel, O and Adams, RP and Ghahramani, Z (2014) Avoiding pathologies in very deep networks. Journal of Machine Learning Research, 33. pp. 202-210. ISSN 1532-4435

Wu, Y and Lobato, JMH and Ghahramani, Z (2014) Gaussian process volatility model. Advances in Neural Information Processing Systems, 2. pp. 1044-1052. ISSN 1049-5258

Hernández-Lobato, JM and Hoffman, MW and Ghahramani, Z (2014) Predictive entropy search for efficient global optimization of black-box functions. Advances in Neural Information Processing Systems, 1. pp. 918-926. ISSN 1049-5258

Lopez-Paz, D and Sra, S and Smola, AJ and Ghahramani, Z and Schölkopf, B (2014) Randomized nonlinear component analysis. 31st International Conference on Machine Learning, ICML 2014, 4. pp. 3196-3204.

Shah, A and Wilson, AG and Ghahramani, Z (2014) Student-t processes as alternatives to Gaussian processes. Journal of Machine Learning Research, 33. pp. 877-885. ISSN 1532-4435

Palla, K and Knowles, DA and Ghahramani, Z (2014) A reversible infinite HMM using normalised random measures. 31st International Conference on Machine Learning, ICML 2014, 5. pp. 4090-4107.

Eaton, F and Ghahramani, Z (2013) Model reductions for inference: generality of pairwise, binary, and planar factor graphs. Neural Comput, 25. pp. 1213-1260.

Darkins, R and Cooke, EJ and Ghahramani, Z and Kirk, PDW and Wild, DL and Savage, RS (2013) Accelerating Bayesian hierarchical clustering of time series data with a randomised algorithm. PLoS One, 8. e59795-.

Ghahramani, Z (2013) Bayesian non-parametrics and the probabilistic approach to modelling. Philos Trans A Math Phys Eng Sci, 371. 20110553-. ISSN 1364-503X

Heaukulani, C and Ghahramani, Z (2013) Dynamic probabilistic models for latent feature propagation in social networks. 30th International Conference on Machine Learning, ICML 2013. pp. 275-283.

Sohn, K-A and Ghahramani, Z and Xing, EP (2012) Robust estimation of local genetic ancestry in admixed populations using a nonparametric Bayesian approach. Genetics, 191. pp. 1295-1308.

Steinhardt, J and Ghahramani, Z (2012) Flexible Martingale Priors for Deep Hierarchies. Journal of Machine Learning Research, 22. pp. 1108-1116.

Cunningham, J and Ghahramani, Z and Rasmussen, CE (2012) Gaussian Processes for time-marked time-series data. Journal of Machine Learning Research, 22. pp. 255-263.

Niu, D and Dy, JG and Ghahramani, Z (2012) A Nonparametric Bayesian Model for Multiple Clustering with Overlapping Feature Views. Journal of Machine Learning Research, 22. pp. 814-822.

Lacoste-Julien, S and Palla, K and Davies, A and Kasneci, G and Graepel, T and Ghahramani, Z (2012) SiGMa: Simple Greedy Matching for Aligning Large Knowledge Bases. arXiv.

Palla, K and Knowles, D and Ghahramani, Z (2012) An Infinite Latent Attribute Model for Network Data. International Conference on Machine Learning.

Poczos, B and Ghahramani, Z and Schneider, J (2012) Copula-based Kernel Dependency Measures. International Conference on Machine Learning.

Kirk, P and Griffin, JE and Savage, RS and Ghahramani, Z and Wild, DL (2012) Bayesian correlated clustering to integrate multiple datasets. Bioinformatics, 28. pp. 3290-3297.

Houlsby, N and Hernández-Lobato, JM and Huszár, F and Ghahramani, Z (2012) Collaborative Gaussian processes for preference learning. Advances in Neural Information Processing Systems, 3. pp. 2096-2104. ISSN 1049-5258

Zhang, Y and Sutton, C and Storkey, A and Ghahramani, Z (2012) Continuous relaxations for discrete Hamiltonian Monte Carlo. Advances in Neural Information Processing Systems, 4. pp. 3194-3202. ISSN 1049-5258

Palla, K and Knowles, DA and Ghahramani, Z (2012) A nonparametric variable clustering model. Advances in Neural Information Processing Systems, 4. pp. 2987-2995. ISSN 1049-5258

Osborne, MA and Duvenaud, D and Garnett, R and Rasmussen, CE and Roberts, SJ and Ghahramani, Z (2012) Active learning of model evidence using Bayesian quadrature. Advances in Neural Information Processing Systems, 1. pp. 46-54. ISSN 1049-5258

Silva, RBDAE and Ghahramani, Z (2012) Bayesian Inference for Gaussian Mixed Graph Models. CoRR, abs/12.

Murray, I and Ghahramani, Z (2012) Bayesian Learning in Undirected Graphical Models: Approximate MCMC algorithms. CoRR, abs/12.

Wood, FD and Griffiths, TL and Ghahramani, Z (2012) A Non-Parametric Bayesian Method for Inferring Hidden Causes. CoRR, abs/12.

Salakhutdinov, R and Roweis, ST and Ghahramani, Z (2012) On the Convergence of Bound Optimization Algorithms. CoRR, abs/12.

Snelson, E and Ghahramani, Z (2012) Variable noise and dimensionality reduction for sparse Gaussian processes. CoRR, abs/12.

Zabih, R and Ghahramani, Z and Kang, SB and Matas, J (2011) Untitled. IEEE T PATTERN ANAL, 33. pp. 865-866. ISSN 0162-8828

Griffiths, TL and Ghahramani, Z (2011) The Indian Buffet Process: An Introduction and Review. J MACH LEARN RES, 12. pp. 1185-1224. ISSN 1532-4435

Zabih, R and Ghahramani, Z and Kang, SB and Matas, J (2011) IEEE Transactions on Pattern Analysis and Machine Intelligence: Editor's note. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33. pp. 865-866. ISSN 0162-8828

Zabih, R and Ghahramani, Z and Kang, SB and Matas, J (2011) Editor's note. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33. pp. 1697-1698. ISSN 0162-8828

Lacoste-Julien, S and Huszar, F and Ghahramani, Z (2011) Approximate inference for the loss-calibrated Bayesian. AISTATS, 15. pp. 416-424.

Zabih, R and Ghahramani, Z and Kang, SB and Matas, J (2011) Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell., 33. pp. 865-866.

Zabih, R and Matas, J and Ghahramani, Z (2011) State of the Journal. IEEE Trans. Pattern Anal. Mach. Intell., 33. pp. 1-2.

Zabih, R and Matas, J and Ghahramani, Z (2010) IEEE Transactions on Pattern Analysis and Machine Intelligence: Editor's note. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32. 1729-. ISSN 0162-8828

Zabih, R and Matas, J and Ghahramani, Z (2010) IEEE Transactions on Pattern Analysis and Machine Intelligence: Editor's Note. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32. pp. 1345-1346. ISSN 0162-8828

Savage, RS and Ghahramani, Z and Griffin, JE and de la Cruz, BJ and Wild, DL (2010) Discovering transcriptional modules by Bayesian data integration. Bioinformatics, 26. i158-i167.

Silva, R and Heller, K and Ghahramani, Z and Airoldi, EM (2010) RANKING RELATIONS USING ANALOGIES IN BIOLOGICAL AND INFORMATION NETWORKS. ANN APPL STAT, 4. pp. 615-644. ISSN 1932-6157

Lippert, C and Ghahramani, Z and Borgwardt, KM (2010) Gene function prediction from synthetic lethality networks via ranking on demand. Bioinformatics, 26. pp. 912-918.

Zabih, R and Matas, J and Ghahramani, Z (2010) IEEE Transactions on Pattern Analysis and Machine Intelligence: Editor's Note. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32. 769-. ISSN 0162-8828

Stegle, O and Denby, KJ and Cooke, EJ and Wild, DL and Ghahramani, Z and Borgwardt, KM (2010) A robust Bayesian two-sample test for detecting intervals of differential gene expression in microarray time series. J Comput Biol, 17. pp. 355-367.

Leskovec, J and Chakrabarti, D and Kleinberg, J and Faloutsos, C and Ghahramani, Z (2010) Kronecker Graphs: An Approach to Modeling Networks. J MACH LEARN RES, 11. pp. 985-1042. ISSN 1532-4435

Wilson, AG and Ghahramani, Z (2010) Generalised Wishart Processes. Uncertainty in Artificial Intelligence (2011).

Ghahramani, Z (2010) Bayesian hidden markov models and extensions: Invited talk. CoNLL 2010 - Fourteenth Conference on Computational Natural Language Learning, Proceedings of the Conference. 56-.

Turner, R and Ghahramani, Z and Bottone, S (2010) Fast online anomaly detection using scan statistics. Proceedings of the 2010 IEEE International Workshop on Machine Learning for Signal Processing, MLSP 2010. pp. 385-390.

Bratières, S and Van Gael, J and Vlachos, A and Ghahramani, Z (2010) Scaling the iHMM: Parallelization versus Hadoop. Proceedings - 10th IEEE International Conference on Computer and Information Technology, CIT-2010, 7th IEEE International Conference on Embedded Software and Systems, ICESS-2010, ScalCom-2010. pp. 1235-1240.

Williamson, S and Orbanz, P and Ghahramani, Z (2010) Dependent Indian Buffet Processes. AISTATS, 9. pp. 924-931.

Zabih, R and Matas, J and Ghahramani, Z (2010) Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell., 32. p. 1729.

Zabih, R and Matas, J and Ghahramani, Z (2010) Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell., 32. pp. 1345-1346.

Zabih, R and Matas, J and Ghahramani, Z (2010) Editor's Note. IEEE Trans. Pattern Anal. Mach. Intell., 32. p. 769.

Adams, RP and Wallach, HM and Ghahramani, Z (2010) Learning the Structure of Deep Sparse Graphical Models. AISTATS, 9. pp. 1-8.

Silva, R and Ghahramani, Z (2009) The hidden life of latent variables: Bayesian learning with mixed graph models. Journal of Machine Learning Research, 10. pp. 1187-1238. ISSN 1532-4435

Adams, RP and Ghahramani, Z (2009) Archipelago: Nonparametric bayesian semi-supervised learning. ACM International Conference Proceeding Series, 382.

Savage, R and Heller, KA and Xu, Y and Ghahramani, Z and Truman, W and Grant, M and Denby, K and Wild, DL (2009) R/BHC: fast Bayesian hierarchical clustering for microarray data. BMC Bioinformatics 2009, 10. ISSN 1471-2105

Van Gael, J and Vlachos, A and Ghahramani, Z (2009) The infinite HMM for unsupervised PoS tagging. EMNLP 2009 - Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: A Meeting of SIGDAT, a Special Interest Group of ACL, Held in Conjunction with ACL-IJCNLP 2009. pp. 678-687.

Eaton, F and Ghahramani, Z (2009) Choosing a Variable to Clamp. AISTATS, 5. pp. 145-152.

Zabih, R and Matas, J and Ghahramani, Z (2009) Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell., 31. pp. 1345-1346.

Zabih, R and Ghahramani, Z and Matas, J (2009) Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell., 31. pp. 961-963.

Rasmussen, CE and de la Cruz, BJ and Ghahramani, Z and Wild, DL (2008) Modeling and visualizing uncertainty in gene expression clusters using dirichlet process mixtures. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 6. pp. 615-628. ISSN 1545-5963

Kriegman, DJ and Fleet, D and Ghahramani, Z (2008) Introduction of new associate editors. IEEE T PATTERN ANAL, 30. p. 561. ISSN 0162-8828

Sung, JM and Ghahramani, Z and Bang, SY (2008) Second-order latent space variational bayes for approximate bayesian inference. IEEE Signal Processing Letters, 15. pp. 918-921. ISSN 1070-9908

Zhang, J and Ghahramani, Z and Yang, YM (2008) Flexible latent variable models for multi-task learning. MACH LEARN, 73. pp. 221-242. ISSN 0885-6125

Sung, JM and Ghahramani, Z and Bang, SY (2008) Latent space variational bayes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30. pp. 2236-2242. ISSN 0162-8828

Kriegman, DJ and Fleet, DJ and Ghahramani, Z (2008) Editorial-State of the Transactions. IEEE Trans. Pattern Anal. Mach. Intell., 30. pp. 193-194.

Kriegman, DJ and Fleet, DJ and Ghahramani, Z (2008) Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell., 30. pp. 2065-2066.

Kriegman, DJ and Fleet, DJ and Ghahramani, Z (2008) Introduction of New Associate Editors. IEEE Trans. Pattern Anal. Mach. Intell., 30. pp. 1505-1506.

Leskovec, J and Chakrabarti, D and Kleinberg, JM and Faloutsos, C and Ghahramani, Z (2008) Kronecker Graphs: An Approach to Modeling Networks. CoRR, abs/08.

Podtelezhnikov, AA and Ghahramani, Z and Wild, DA (2007) Learning about protein hydrogen bonding by minimizing contrastive divergence. Proteins: Structure, Function, and Bioinformatics, 66. pp. 588-599. ISSN 0887-3585

Beal, MJ and Li, J and Ghahramani, Z and Wild, DL (2007) Reconstructing transcriptional networks using gene expression profiling and bayesian state-space models. pp. 217-241.

Silva, RBDAE and Heller, KA and Ghahramani, Z (2007) Analogical Reasoning with Relational Bayesian Sets. AISTATS, 2. pp. 500-507.

Snelson, E and Ghahramani, Z (2007) Local and global sparse Gaussian process approximations. AISTATS, 2. pp. 524-531.

Heller, KA and Ghahramani, Z (2007) A Nonparametric Bayesian Approach to Modeling Overlapping Clusters. AISTATS, 2. pp. 187-194.

Teh, YW and Görür, D and Ghahramani, Z (2007) Stick-breaking Construction for the Indian Buffet Process. AISTATS, 2. pp. 556-563.

Chu, W and Ghahramani, Z and Wild, DL (2006) Bayesian segmental models with multiple sequence alignment profiles for protein secondary structure and contact map prediction. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 3. pp. 98-113. ISSN 1545-5963

Beal, MJ and Ghahramani, Z (2006) Variational Bayesian learning of directed graphical models with hidden variables. Bayesian Analysis, 1. pp. 793-832. ISSN 1936-0975

Kim, HC and Kim, D and Ghahramani, Z and Bang, SY (2006) Appearance-based gender classification with Gaussian processes. Pattern Recognition Letters, 27. pp. 618-626. ISSN 0167-8655

Azran, A and Ghahramani, Z (2006) A new approach to data driven clustering. ICML 2006 - Proceedings of the 23rd International Conference on Machine Learning, 2006. pp. 57-64.

KIM, HC and Ghahramani, Z (2006) Bayesian gaussian process classification with the EM-EP algorithm. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28. pp. 1948-1959. ISSN 0162-8828

Beal, MJ and Falciani, FL and Ghahramani, Z and Rangel, C and Wild, DL (2005) A Bayesian approach to reconstructing genetic regulatory networks with hidden factors. Bioinformatics, 21. pp. 349-356. ISSN 1367-4803

Penny, W and Ghahramani, Z and Friston, K (2005) Bilinear dynamical systems. Philisophical Transactions of the Royal Society of London, Series B: Biological Sciences, 360. pp. 983-994. ISSN 0962-8436

Chu, W and Ghahramani, Z and Falciani, F and Wild, DL (2005) Biomarker discovery in microarray gene expression data with Gaussian processes. Bioinformatics, 21. pp. 3385-3393. ISSN 1367-4803

Chu, W and Ghahramani, Z (2005) Gaussian processes for ordinal regression. Journal of Machine Learning Research, 6. pp. 1019-1042. ISSN 1532-4435

Cowell, R and Ghahramani, Z (2005) Preface. AISTATS 2005 - Proceedings of the 10th International Workshop on Artificial Intelligence and Statistics.

Rangel, C and Angus, J and Ghahramani, Z and Lioumi, M and Southeran, E and Gaiba, A and Wild, DL and Falciani, F (2004) Modeling T-cell activation using gene expression profiling and state space models. Bioinformatics, 20. pp. 1361-1372. ISSN 1367-4803

Rangel, C and Angus, J and Ghahramani, Z and Lioumi, M and Southeran, E and Gaiba, A and Wild, DL and Falciani, F (2004) Modeling T-cell activation using gene expression profiling and state-space models. Bioinformatics, 20. pp. 1361-1372. ISSN 1367-4803

Thrun, S and Liu, Y and Koller, D and Ng, AY and Ghahramani, Z and Durrant Whyte, H (2004) Simultaneous localization and mapping with sparse extended information filters. International Journal of Robotics Research, 23. pp. 693-716. ISSN 0278-3649

Todorov, E and Ghahramani, Z (2003) Unsupervised learning of sensory-motor primitives. IEEE Engineering in Medicine and Biology Society: Proceedings of the 25th Annual International Conference of the IEEE, 25. pp. 1750-1753. ISSN 1094-687X

Ueda, N and Ghahramani, Z (2002) Bayesian model search for mixture models based on optimizing variational bounds. Neural Networks, 15. pp. 1223-1241. ISSN 0893-6080

Raval, A and Ghahramani, Z and Wild, DL (2002) A Bayesian network model for protein fold and remote homologue recognition. Bioinformatics, 18. pp. 788-801. ISSN 1460-2059

Korenberg, AT and Ghahramani, Z (2002) A Bayesian view of motor adaptation. Current Psychology of Cognition, 21. pp. 537-564. ISSN 0249-9185

Korenberg, AT and Ghahramani, Z (2002) A Bayesian view of motor adaptation. CAH PSYCHOL COGN, 21. pp. 537-564. ISSN 0249-9185

Wolpert, DM and Ghahramani, Z and Flanagan, JR (2001) Perspectives and problems in motor learning. Trends in Cognitive Sciences, 5. pp. 487-494. ISSN 1364-6613

Ghahramani, Z (2001) An introduction to hidden Markov models and Bayesian networks. International Journal of Pattern Recognition and Artificial Intelligence, 15. pp. 9-42. ISSN 0218-0014

Wolpert, DM and Ghahramani, Z and Flanagan, JR (2001) Perspectives and problems in motor learning. Trends in Cognitive Sciences, 5. pp. 487-494. ISSN 1364-6613

Wolpert, DM and Ghahramani, Z (2000) Computational principles of movement neuroscience. Nature Neuroscience, 3. pp. 1212-1217. ISSN 1097-6256

Wolpert, DM and Ghahramani, Z (2000) Computational principles of movement neuroscience. Nature Neuroscience, 3. pp. 1212-1217. ISSN 1097-6256

Ueda, N and Nakano, R and Ghahramani, Z and Hinton, GE (2000) SMEM algorithm for mixture models. Neural Computation, 12. pp. 2109-2128. ISSN 0899-7667

Ueda, N and Nakano, R and Ghahramani, Z and Hinton, GE (2000) Split and merge EM algorithm for improving Gaussian mixture density estimates. Journal of VLSI Signal Processing, 26. pp. 133-140. ISSN 0922-5773

Ghahramani, Z (2000) Variational Bayesian learning. Bulletin of the Italian Artificial Intelligence Association (AI/IA Notizie), 13. pp. 13-18.

Ghahramani, Z and Hinton, GE (2000) Variational learning for switching state-space models. Neural Computation, 12. pp. 831-864. ISSN 0899-7667

Ghahramani, Z (2000) Building blocks of movement. Nature, 407. pp. 682-683. ISSN 0028-0836

Ghahramani, Z (2000) Computational neuroscience: building blocks of movement. Nature, 407. pp. 682-683. ISSN 0028-0836

Jordan, MI and Ghahramani, Z and Jaakola, TS and Saul, LK (1999) An introduction to variational methods for graphical models. Machine Learning, 37. pp. 183-233. ISSN 0885-6125

Roweis, ST and Ghahramani, Z (1999) A Unifying Review of Linear Gaussian Models. Neural Computation, 11. pp. 305-345. ISSN 0899-7667

Ghahramani, Z and Jordan, MI (1997) Factorial hidden Markov models. Machine Learning, 29. pp. 245-273. ISSN 0885-6125

Ghahramani, Z and Wolpert, DM (1997) Modular decomposition in visuomotor learning. Nature - London, 386. pp. 392-395. ISSN 0028-0836

Hinton, GE and Ghahramani, Z (1997) Generative models for discovering sparse distributed representations. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 352. pp. 1177-1190. ISSN 0962-8436

Ghahramani, Z and Wolpert, DM (1997) Modular decomposition in visuomotor learning. Nature, 386. pp. 392-394. ISSN 0028-0836

Cohn, DA and Ghahramani, Z and Jordan, MI (1996) Active learning with statistical models. Journal of Artificial Intelligence Research, 4. pp. 129-145. ISSN 1076-9757

Ghahramani, Z and Wolpert, DM and Jordan, MI (1996) Generalization to local remappings of the visuomotor coordinate transformation. Journal of Neuroscience, 16. pp. 7085-7096. ISSN 0270-6474

Ghahramani, Z and Wolpert, DM and Jordan, MI (1996) Generalization to local remappings of the visuomotor coordinate transformation. Journal of Neuroscience, 16. pp. 7085-7096. ISSN 0270-6474

Cohn, DA and Ghahramani, Z and Jordan, MI (1996) Active Learning with Statistical Models. CoRR, cs.AI/.

Wolpert, DM and Ghahramani, Z and Jordan, MI (1995) An internal model for sensorimotor integration. Science, 269. pp. 1880-1882. ISSN 0036-8075

Wolpert, DM and Ghahramani, Z and Jordan, MI (1995) Are arm trajectories planned in kinematic or dynamic coordinates? An adaptation study. Experimental Brain Research, 103. pp. 460-470. ISSN 0014-4819

Wolpert, DM and Ghahramani, Z and Jordan, MI (1995) Are arm trajectories planned in kinematic or dynamic coordinates? An adaptation study. Experimental Brain Research, 103. pp. 460-470. ISSN 0014-4819

Ghahramani, Z and Wolpert, DM and Jordan, MI (1995) Computational principles of multisensory integration: studies of adaptation to novel visuo-auditory remappings. Society for Neuroscience Abstracts, 21. p.1181-.

Wolpert, DM and Ghahramani, Z and Jordan, MI (1995) An internal model for sensorimotor integration. Science, 269. pp. 1880-1882. ISSN 0036-8075

Wolpert, DM and Ghahramani, Z and Jordan, MI (1994) Perceptual distortion contributes to the curvature of human reaching movements. Experimental Brain Research, 98. pp. 153-156. ISSN 0014-4819

Wolpert, DM and Ghahramani, Z and Jordan, MI (1994) Perceptual distortion contributes to the curvature of human reaching movements. Experimental Brain Research, 98. pp. 153-156. ISSN 0014-4819

Bradshaw, J and Matthews, AGDG and Ghahramani, Z Adversarial Examples, Uncertainty, and Transfer Testing Robustness in Gaussian Process Hybrid Deep Networks. (Unpublished)

Houlsby, N and Huszár, F and Ghahramani, Z and Lengyel, M Bayesian Active Learning for Classification and Preference Learning. (Unpublished)

Gal, Y and Ghahramani, Z Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference. (Unpublished)

Bratieres, S and Quadrianto, N and Ghahramani, Z Bayesian Structured Prediction Using Gaussian Processes. (Unpublished)

Mohamed, S and Heller, K and Ghahramani, Z Bayesian and L1 Approaches to Sparse Unsupervised Learning. (Unpublished)

Borgwardt, KM and Ghahramani, Z Bayesian two-sample tests. (Unpublished)

Heaukulani, C and Knowles, DA and Ghahramani, Z Beta diffusion trees and hierarchical feature allocations. (Unpublished)

Matthews, AGDG and Ghahramani, Z Classification using log Gaussian Cox processes. (Unpublished)

Wilson, AG and Ghahramani, Z Copula Processes. (Unpublished)

Gal, Y and Islam, R and Ghahramani, Z Deep Bayesian Active Learning with Image Data. (Unpublished)

Ścibior, A and Kammar, O and Vákár, M and Staton, S and Yang, H and Cai, Y and Ostermann, K and Moss, SK and Heunen, C and Ghahramani, Z Denotational validation of higher-order Bayesian inference. Proc. ACM Program. Lang. 2, POPL, Article 60 (January 2018). (Unpublished)

Shah, A and Ghahramani, Z Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering. (Unpublished)

Ge, H and Gal, Y and Ghahramani, Z Dirichlet Fragmentation Processes. (Unpublished)

Zhe, S and Zhang, K and Wang, P and Lee, K-C and Xu, Z and Qi, Y and Ghahramani, Z Distributed Flexible Nonlinear Tensor Factorization. (Unpublished)

Wu, Y and Hernández-Lobato, JM and Ghahramani, Z Dynamic Covariance Models for Multivariate Financial Time Series. (Unpublished)

Zhang, Y and Hernández-Lobato, JM Ergodic Inference: Accelerate Convergence by Optimisation. (Unpublished)

Wilson, AG and Knowles, DA and Ghahramani, Z Gaussian Process Regression Networks. (Unpublished)

Lopez-Paz, D and Hernández-Lobato, JM and Ghahramani, Z Gaussian Process Vine Copulas for Multivariate Dependence. (Unpublished)

Valera, I and Pradier, MF and Ghahramani, Z General Latent Feature Modeling for Data Exploration Tasks. (Unpublished)

Valera, I and Pradier, MF and Lomeli, M and Ghahramani, Z General Latent Feature Models for Heterogeneous Datasets. (Unpublished)

Savage, RS and Ghahramani, Z and Griffin, JE and Kirk, P and Wild, DL Identifying cancer subtypes in glioblastoma by combining genomic, transcriptomic and epigenomic data. International Conference on Machine Learning (ICML) 2012: Workshop on Machine Learning in Genetics and Genomics. (Unpublished)

Iwata, T and Ghahramani, Z Improving Output Uncertainty Estimation and Generalization in Deep Learning via Neural Network Gaussian Processes. (Unpublished)

Adams, RP and Wallach, HM and Ghahramani, Z Learning the Structure of Deep Sparse Graphical Models. (Unpublished)

Tripuraneni, N and Gu, S and Ge, H and Ghahramani, Z A Linear-Time Particle Gibbs Sampler for Infinite Hidden Markov Models. (Unpublished)

Knowles, D and Ghahramani, Z Nonparametric Bayesian sparse factor models with application to gene expression modeling. Annals of Applied Statistics, 5. pp. 1534-1552. (Unpublished)

Burgess, J and Lloyd, JR and Ghahramani, Z One-Shot Learning in Discriminative Neural Networks. (Unpublished)

Knowles, DA and Ghahramani, Z Pitman-Yor Diffusion Trees. (Unpublished)

Peharz, R and Vergari, A and Stelzner, K and Molina, A and Trapp, M and Kersting, K and Ghahramani, Z Probabilistic Deep Learning using Random Sum-Product Networks. (Unpublished)

Davies, A and Ghahramani, Z The Random Forest Kernel and other kernels for big data from random partitions. (Unpublished)

Williamson, S and Ghahramani, Z and MacEachern, SN and Xing, EP Restricting exchangeable nonparametric distributions. (Unpublished)

Grosse, RB and Ghahramani, Z and Adams, RP Sandwiching the marginal likelihood using bidirectional Monte Carlo. (Unpublished)

Reed, C and Ghahramani, Z Scaling the Indian Buffet Process via Submodular Maximization. In ICML 2013: JMLR W&CP 28 (3): 1013-1021, 2013. (Unpublished)

Ranca, R and Ghahramani, Z Slice Sampling for Probabilistic Programming. (Unpublished)

Duvenaud, D and Lloyd, JR and Grosse, R and Tenenbaum, JB and Ghahramani, Z Structure Discovery in Nonparametric Regression through Compositional Kernel Search. (Unpublished)

Chen, Y and Mansinghka, V and Ghahramani, Z Sublinear-Time Approximate MCMC Transitions for Probabilistic Programs. (Unpublished)

Quadrianto, N and Sharmanska, V and Knowles, DA and Ghahramani, Z The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. (Unpublished)

Adams, RP and Ghahramani, Z and Jordan, MI Tree-Structured Stick Breaking Processes for Hierarchical Data. (Unpublished)

Hron, J and Matthews, AGDG and Ghahramani, Z Variational Gaussian Dropout is not Bayesian. (Unpublished)

Iwata, T and Duvenaud, D and Ghahramani, Z Warped Mixtures for Nonparametric Cluster Shapes. (Unpublished)

Iwata, T and Duvenaud, D and Ghahramani, Z Warped Mixtures for Nonparametric Cluster Shapes. (Unpublished)

Palla, K and Knowles, DA and Ghahramani, Z A dependent partition-valued process for multitask clustering and time evolving network modelling. (Unpublished)

Dziugaite, GK and Ghahramani, Z and Roy, DM A study of the effect of JPG compression on adversarial images. (Unpublished)

Book Section

Ghahramani, Z and Mohamed, S and Heller, KA (2014) Partial Membership and Factor Analysis. In: Handbook of Mixed Membership Models and Their Applications. Chapman and Hall/CRC, pp. 67-88.

Van Gael, J and Ghahramani, Z (2011) Nonparametric hidden Markov models. In: Bayesian Time Series Models. UNSPECIFIED, pp. 317-340.

Perez Cruz, F and Ghahramani, Z and Pontil, M (2007) Kernel conditional graphical models. In: Predicting Structured Data. MIT Press, Cambridge, MA, USA, pp. 265-282.

Ghahramani, Z and Heller, KA (2006) Bayesian sets. In: Advances in Neural Information Processing Systems 18. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 435-442.

Chu, W and Keerthi, SS and Ong, CJ and Ghahramani, Z (2006) Bayesian support vector machines for feature ranking and selection. In: Feature Extraction, Foundations and Applications. Studies in Fuzziness and Soft Computing, 207 . Springer, pp. 403-416.

Zhu, X and Kandola, J and Lafferty, J and Ghahramani, Z (2006) Graph kernels by spectral transforms. In: Semi-Supervised Learning, Chapter 15. MIT Press, Cambridge, MA, USA, pp. 277-289.

Griffiths, TL and Ghahramani, Z (2006) Infinite latent feature models and the Indian buffet process. In: Advances in Neural Information Processing Systems 18. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 475-482.

Zhang, J and Ghahramani, Z and Yang, Y (2006) Learning multiple related tasks using latent independent component analysis. In: Advances in Neural Information Processing Systems 18. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 1585-1592.

Murray, I and McKay, DJC and Ghahramani, Z (2006) Nested sampling for Potts models. In: Advances in Neural Information Processing Systems 18. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 947-954.

Snelson, E and Ghahramani, Z (2006) Sparse Gaussian processes using pseudo-inputs. In: Advances in Neural Information Processing Systems 18. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 1257-1264.

Rangel, C and Angus, J and Ghahramani, Z and Wild, DL (2005) Modeling genetic regulatory networks using gene expression profiling and state space models. In: Probabilistic Modelling in Bioinformatics and Medical Informatics. Springer, pp. 269-293.

Zhu, X and Kandola, J and Ghahramani, Z and Lafferty, J (2005) Nonparametric transforms of graph kernels for semi-supervised learning. In: Advances in Neural Information Processing Systems 17. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 1641-1648.

Beal, MJ and Li, J and Ghahramani, Z and Wild, DL (2005) Reconstructing transcriptional networks using gene expression profiling and Bayesian state space models. In: Introduction to Systems Biology. Humana Press (Springer), Chapter 12-.

Zhang, J and Ghahramani, Z and Yang, Y (2005) A probabilistic model for online document clustering with application to novelty detection. In: Advances in Neural Information Processing Systems 17. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 1617-1624.

Wolpert, DM and Ghahramani, Z (2004) Computational motor control. In: The Cognitive Neurosciences. MIT Press, Cambridge, MA, USA.

Thrun, S and Koller, D and Ghahramani, Z and Durrant Whyte, H and Ng, AY (2004) Simultaneous mapping and localization with sparse extended information filters. In: Algorithmic Foundations of Robotics V. Springer Tracts in Advanced Robotics . Springer, pp. 363-380.

Ghahramani, Z (2004) Unsupervised learning. In: Advanced Lectures on Machine Learning: ML Summer Schools 2003. Lecture Notes in Computer Science: Lecture Notes in Artificial Intelligence, 3176 . Springer, Berlin, Germany, pp. 72-112.

Wolpert, DM and Ghahramani, Z (2004) Bayes rule in perception, action and cognition. In: The Oxford Companion to the Mind. Oxford University Press.

Ghahramani, Z (2003) Information theory. In: Encyclopedia of Cognitive Science. Nature Publishing Group, London, UK.

Jin, R and Ghahramani, Z (2003) Learning with multiple labels. In: Advances in Neural Information Processing Systems 15. MIT Press, Cambridge, MA, USA, pp. 921-928.

Wolpert, DM and Ghahramani, Z (2003) Motor learning models. In: Encyclopedia of Cognitive Science. Nature Publishing Group, London, UK.

Ghahramani, Z (2002) Graphical models: parameter learning. In: The Handbook of Brain Theory and Neural Networks. Bradford Books . MIT Press.

Ghahramani, Z and Beal, MJ (2001) Graphical models and variational methods. In: Advanced Mean Field Methods: Theory and Practice. Neural Information Processing Series . MIT Press, Cambridge, MA, USA, pp. 161-177.

Roweis, ST and Ghahramani, Z (2001) Learning nonlinear dynamical systems using the expectation-maximization algorithm. In: Kalman Filtering and Neural Networks. Wiley and Sons, pp. 175-220.

Ghahramani, Z and Beal, MJ (2001) Propagation algorithms for variational Bayesian learning. In: Advances in Neural Information Processing Systems 13. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 507-513.

Ghahramani, Z (2001) An introduction to hidden Markov models and Bayesian networks. In: Hidden Markov Models: Applications in Computer Vision. Series in Machine Perception and Artificial Intelligence, 45 . World Scientific Publishing, -.

Hinton, GE and Ghahramani, Z and Teh, YN (2000) Learning to parse images. In: Advances in Neural Information Processing Systems 12. Bradford Series . MIT Press, pp. 463-469.

Wolpert, DM and Ghahramani, Z (2000) Maps, modules, and internal models in human motor control. In: Biomechanics and Neural Control of Posture and Movement, Chapter 23. Springer, New York, USA, pp. 317-324.

Ghahramani, Z and Beal, MJ (2000) Variational inference for Bayesian mixture of factor analysers. In: Advances in Neural Information Processing Systems 12. Bradford Series . MIT Press, pp. 449-455.

Ghahramani, Z and Roweis, S (1999) Learning nonlinear dynamical systems using an EM algorithm. In: Advances in Neural Information Processing Systems 11. MIT Press, Cambridge, MA, USA, pp. 431-437.

Ueda, N and Nakano, R and Ghahramani, Z and Hinton, GE (1999) SMEM algorithm for mixture models. In: Advances in Neural Information Processing Systems 11. MIT Press, Cambridge, MA, USA, pp. 599-605.

Ghahramani, Z (1999) Time for bayes: comments to Amari and Kohonen. In: Bulletin of the 52nd Seesion of the International Statistical Institute. International Statistical Institute, Finland, pp. 115-116.

Ghahramani, Z and Hinton, GE (1998) Hierarchical non-linear factor analysis and topographic maps. In: Advances in Neural Information Processing Systems 10. Bradford Series . MIT Press, Cambridge, MA, USA, Part III-.

Ghahramani, Z (1998) Learning dynamic Bayesian networks. In: Adaptive Processing of Sequences and Data Structures: International Summer School on Neural Networks. Lecture Notes in Computer Science: Lecture notes in Artificial Intelligence, 1387 . Springer, Berlin, Germany, pp. 168-197.

Sallans, B and Hinton, GE and Ghahramani, Z (1998) A hierarchical community of experts. In: Neural Networks and Machine Learning. NATO ASI Series F: Computer and Systems Sciences . Springer, Berlin, Germany, pp. 269-284.

Hinton, GE and Sallans, B and Ghahramani, Z (1998) A hierarchical community of experts. In: Learning in Graphical Models. NATO ASI Series D: Behavioural and Social Sciences, 89 . Kluwer Academic Publishers, Boston, MA, USA, pp. 474-494.

Jordan, MI and Ghahramani, Z and Jaakola, TS and Saul, LK (1998) An introduction to variational methods in graphical models. In: Learning in Graphical Models. NATO ASI Series D: Behavioural and Social Sciences, 89 . Kluwer Academic Publishers, Boston, MA, USA, pp. 105-161.

Cohn, DA and Ghahramani, Z and Jordan, MI (1997) Active learning with mixture models. In: Multiple Model Approaches to Modelling and Control. Taylor and Francis, London, UK, pp. 167-183.

Ghahramani, Z and Wolpert, DM and Jordan, MI (1997) Computational models of sensorimotor integration. In: Self-Organization, Computational Maps, and Motor Control. Advances in Psychology, 119 . North Holland Publishing Company, Amsterdam, Netherlands, pp. 117-147.

Jordan, MI and Ghahramani, Z and Saul, LK (1997) Hidden Markov decision trees. In: Advances in Neural Information Processing Systems 9. Bradford Series . MIT Press, pp. 501-507.

Ghahramani, Z and Jordan, MI (1997) Mixture models for learning from incomplete data. In: Making Learning Systems Practical. Computational Learning Theory and Natural Learning Systems., 4 . MIT Press, Cambridge, MA, USA, pp. 67-85.

Ghahramani, Z and Jordan, MI (1996) Factorial hidden Markov models. In: Advances in Neural Information Processing Systems 8. MIT Press, Cambridge, MA, USA, pp. 472-478.

Cohn, DA and Ghahramani, Z and Jordan, MI (1995) Active learning with statistical models. In: Advances in Neural Information Processing Systems 7. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 705-712.

Ghahramani, Z and Wolpert, DM and Jordan, MI (1995) Computational structure of coordinate transformations: a generalization study. In: Advances in Neural Information Processing Systems 7. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 1125-1132.

Ghahramani, Z (1995) Factorial learning and the EM algorithm. In: Advances in Neural Information Processing Systems 7. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 617-624.

Wolpert, DM and Ghahramani, Z and Jordan, MI (1995) Forward dynamic models in human motor control: psychophysical evidence. In: Advances in Neural Information Processing Systems 7. Bradford Series . MIT Press, Cambridge, MA, USA, pp. 43-50.

Ghahramani, Z and Jordan, MI (1995) Supervised learning from incomplete data using an EM approach. In: Advances in Neural Information Processing Systems 6. Morgan Kaufmann Publishers, pp. 120-127.

Conference or Workshop Item

Gu, S and Lillicrap, T and Ghahramani, Z and Turner, RE and Levine, S (2019) Q-PrOP: Sample-efficient policy gradient with an off-policy critic. In: UNSPECIFIED.

Tucker, G and Bhupatiraju, S and Gu, S and Turner, RE and Ghahramani, Z and Levine, S (2018) The Mirage of Action-Dependent Baselines in Reinforcement Learning. In: ICML 2018: 35th International Conference on Machine Learning, 2018-7-10 to 2018-7-15, Stockholm, Sweden pp. 5015-5024..

De Matthews, AGG and Hron, J and Rowland, M and Turner, RE and Ghahramani, Z (2018) Gaussian process behaviour in wide deep neural networks. In: 6th International Conference on Learning Representations, 2018-4-30 to --.

Ge, H and Xu, K and Ghahramani, Z (2018) Turing: Composable inference for probabilistic programming. In: UNSPECIFIED pp. 1682-1690..

Valera, I and Ghahramani, Z (2017) Automatic discovery of the statistical types of variables in a dataset. In: UNSPECIFIED pp. 5380-5388..

Gal, Y and Islam, R and Ghahramani, Z (2017) Deep Bayesian active learning with image data. In: UNSPECIFIED pp. 1923-1932..

Gu, S and Lillicrap, T and Ghahramani, Z and Turner, RE and Schölkopf, B and Levine, S (2017) Interpolated policy gradient: Merging on-policy and off-policy gradient estimation for deep reinforcement learning. In: UNSPECIFIED pp. 3847-3856..

Balog, M and Tripuraneni, N and Ghahramani, Z and Weiler, A (2017) Lost relatives of the Gumbel trick. In: UNSPECIFIED pp. 588-606..

Palla, K and Knowles, D and Ghahramani, Z (2017) A birth-death process for feature allocation. In: UNSPECIFIED pp. 4209-4237..

Valera, I and Ghahramani, Z (2017) Automatic Discovery of the Statistical Types of Variables in a Dataset. In: ICML 2017, 2017-8-6 to 2017-8-11, International Conference Centre, Sydney Australia pp. 3521-3529..

Palla, K and Knowles, DA and Ghahramani, Z (2017) A Birth-Death Process for Feature Allocation. In: ICML 2017, 2017-8-6 to 2017-8-11, International Conference Centre, Sydney Australia pp. 2751-2759..

Ghahramani, Z and Gal, Y and Islam, R (2017) Deep Bayesian Active Learning with Image Data. In: ICML 2017, 2017-8-6 to 2017-8-11, Sydney, Australia pp. 1183-1192.. (Unpublished)

Ghahramani, Z (2016) Automating machine learning. In: UNSPECIFIED XX-..

Shah, A and Ghahramani, Z (2016) Markov beta processes for time evolving dictionary learning. In: UNSPECIFIED pp. 676-685..

Shah, A and Ghahramani, Z (2016) Pareto frontier learning with expensive correlated objectives. In: UNSPECIFIED pp. 2839-2849..

Gal, Y and Ghahramani, Z (2016) Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning. In: UNSPECIFIED pp. 1050-1059..

Shah, A and Ghahramani, Z (2016) Pareto Frontier Learning with Expensive Correlated Objectives. In: UNSPECIFIED pp. 1919-1927..

Chen, Y and Ghahramani, Z (2016) Scalable Discrete Sampling as a Multi-Armed Bandit Problem. In: UNSPECIFIED pp. 2492-2501..

Gal, Y and Ghahramani, Z (2016) A Theoretically Grounded Application of Dropout in Recurrent Neural Networks. In: UNSPECIFIED pp. 1019-1027..

͆cibior, A and Ghahramani, Z and Gordon, AD (2015) Practical probabilistic programming with monads. In: UNSPECIFIED pp. 165-176..

Ge, H and Chen, Y and Wan, M and Ghahramani, Z (2015) Distributed inference for Dirichlet process mixture models. In: UNSPECIFIED pp. 2266-2274..

Steinruecken, C and Ghahramani, Z and MacKay, D (2015) Improving PPM with Dynamic Parameter Updates. In: UNSPECIFIED pp. 193-202..

Tripuraneni, N and Gu, S and Ge, H and Ghahramani, Z (2015) Particle Gibbs for infinite Hidden Markov models. In: UNSPECIFIED pp. 2395-2403..

Lloyd, JR and Ghahramani, Z (2015) Statistical model criticism using kernel two sample tests. In: UNSPECIFIED pp. 829-837..

Dziugaite, GK and Roy, DM and Ghahramani, Z (2015) Training generative neural networks via maximum mean discrepancy optimization. In: UNSPECIFIED pp. 258-267..

Hernández-Lobato, D and Hernández-Lobato, JM and Ghahramani, Z (2015) A probabilistic model for dirty multi-task feature selection. In: UNSPECIFIED pp. 1073-1082..

Ge, H and Chen, Y and Wan, M and Ghahramani, Z (2015) Distributed Inference for Dirichlet Process Mixture Models. In: UNSPECIFIED pp. 2276-2284..

Shah, A and Knowles, DA and Ghahramani, Z (2015) An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process. In: UNSPECIFIED pp. 1594-1603..

Shah, A and Ghahramani, Z (2015) Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions. In: UNSPECIFIED pp. 3330-3338..

Heaukulani, C and Knowles, DA and Ghahramani, Z (2014) Beta diffusion trees. In: UNSPECIFIED pp. 3821-3829..

Houlsby, N and Hernández-Lobato, JM and Ghahramani, Z (2014) Cold-start active learning with robust ordinal matrix factorization. In: UNSPECIFIED pp. 1964-1972..

Valera, I and Ghahramani, Z (2014) General table completion using a Bayesian nonparametric model. In: UNSPECIFIED pp. 981-989..

Gal, Y and Ghahramani, Z (2014) Pitfalls in the use of parallel inference for the dirichlet process. In: UNSPECIFIED pp. 1437-1445..

Welling, M and Ghahramani, Z and Cortes, C and Lawrence, N and Weinberger, K (2014) Preface. In: UNSPECIFIED xxxi-xxxiv..

Hernández-Lobato, JM and Houlsby, N and Ghahramani, Z (2014) Probabilistic matrix factorization with non-random missing data. In: UNSPECIFIED pp. 3394-3436..

Bratières, S and Quadrianto, N and Nowozin, S and Ghahramani, Z (2014) Scalable Gaussian process structured prediction for grid factor graph applications. In: UNSPECIFIED pp. 1625-1636..

Hernández-Lobato, JM and Houlsby, N and Ghahramani, Z (2014) Stochastic inference for scalable probabilistic modeling of binary matrices. In: UNSPECIFIED pp. 1693-1710..

Bargi, A and Da Xu, RY and Ghahramani, Z and Piccardi, M (2014) A non-parametric conditional factor regression model for multi-dimensional input and response. In: UNSPECIFIED pp. 77-85..

(2014) Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, December 8-13 2014, Montreal, Quebec, Canada. In: UNSPECIFIED.

Lloyd, JR and Duvenaud, DK and Grosse, RB and Tenenbaum, JB and Ghahramani, Z (2014) Automatic Construction and Natural-Language Description of Nonparametric Regression Models. In: UNSPECIFIED pp. 1242-1250..

Duvenaud, DK and Rippel, O and Adams, RP and Ghahramani, Z (2014) Avoiding pathologies in very deep networks. In: UNSPECIFIED pp. 202-210..

Heaukulani, C and Knowles, DA and Ghahramani, Z (2014) Beta Diffusion Trees. In: UNSPECIFIED pp. 1809-1817..

Houlsby, N and Hernández-Lobato, JM and Ghahramani, Z (2014) Cold-start Active Learning with Robust Ordinal Matrix Factorization. In: UNSPECIFIED pp. 766-774..

Gal, Y and Ghahramani, Z (2014) Pitfalls in the use of Parallel Inference for the Dirichlet Process. In: UNSPECIFIED pp. 208-216..

Hernández-Lobato, JM and Hoffman, MW and Ghahramani, Z (2014) Predictive Entropy Search for Efficient Global Optimization of Black-box Functions. In: UNSPECIFIED pp. 918-926..

Hernández-Lobato, JM and Houlsby, N and Ghahramani, Z (2014) Probabilistic Matrix Factorization with Non-random Missing Data. In: UNSPECIFIED pp. 1512-1520..

Lopez-Paz, D and Sra, S and Smola, AJ and Ghahramani, Z and Schölkopf, B (2014) Randomized Nonlinear Component Analysis. In: UNSPECIFIED pp. 1359-1367..

Bratieres, S and Quadrianto, N and Nowozin, S and Ghahramani, Z (2014) Scalable Gaussian Process Structured Prediction for Grid Factor Graph Applications. In: UNSPECIFIED pp. 334-342..

Hernández-Lobato, JM and Houlsby, N and Ghahramani, Z (2014) Stochastic Inference for Scalable Probabilistic Modeling of Binary Matrices. In: UNSPECIFIED pp. 379-387..

Shah, A and Wilson, AG and Ghahramani, Z (2014) Student-t Processes as Alternatives to Gaussian Processes. In: UNSPECIFIED pp. 877-885..

Knowles, DA and Ghahramani, Z and Palla, K (2014) A reversible infinite HMM using normalised random measures. In: UNSPECIFIED pp. 1998-2006..

Iwata, T and Houlsby, N and Ghahramani, Z (2013) Active learning for interactive visualization. In: UNSPECIFIED pp. 342-350..

(2013) Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013, Lake Tahoe, Nevada, United States. In: UNSPECIFIED.

Shah, A and Ghahramani, Z (2013) Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering. In: UNSPECIFIED.

Iwata, T and Shah, A and Ghahramani, Z (2013) Discovering latent influence in online social activities via shared cascade poisson processes. In: UNSPECIFIED pp. 266-274..

Wu, Y and Hernández-Lobato, JM and Ghahramani, Z (2013) Dynamic Covariance Models for Multivariate Financial Time Series. In: UNSPECIFIED pp. 558-566..

Lopez-Paz, D and Hernández-Lobato, JM and Ghahramani, Z (2013) Gaussian Process Vine Copulas for Multivariate Dependence. In: UNSPECIFIED pp. 10-18..

Lacoste-Julien, S and Palla, K and Davies, A and Kasneci, G and Graepel, T and Ghahramani, Z (2013) SIGMa: simple greedy matching for aligning large knowledge bases. In: UNSPECIFIED pp. 572-580..

Reed, C and Ghahramani, Z (2013) Scaling the Indian Buffet Process via Submodular Maximization. In: UNSPECIFIED pp. 1013-1021..

Duvenaud, DK and Lloyd, JR and Grosse, RB and Tenenbaum, JB and Ghahramani, Z (2013) Structure Discovery in Nonparametric Regression through Compositional Kernel Search. In: UNSPECIFIED pp. 1166-1174..

Quadrianto, N and Sharmanska, V and Knowles, DA and Ghahramani, Z (2013) The Supervised IBP: Neighbourhood Preserving Infinite Latent Feature Models. In: UNSPECIFIED.

Bousmalis, K and Zafeiriou, S and Morency, L-P and Pantic, M and Ghahramani, Z (2013) Variational Hidden Conditional Random Fields with Coupled Dirichlet Process Mixtures. In: UNSPECIFIED pp. 531-547..

Póczos, B and Ghahramani, Z and Schneider, JG (2012) Copula-based Kernel Dependency Measures. In: UNSPECIFIED.

Mohamed, S and Heller, KA and Ghahramani, Z (2012) Evaluating Bayesian and L1 Approaches for Sparse Unsupervised Learning . In: UNSPECIFIED.

Wilson, AG and Ghahramani, Z (2012) Modelling Input Varying Correlations between Multiple Responses. In: UNSPECIFIED pp. 858-861..

Doshi-Velez, F and Ghahramani, Z (2011) A Comparison of Human and Agent Reinforcement Learning in Partially Observable Domains. In: UNSPECIFIED.

Bahramisharif, A and Gerven, MAJV and Schoffelen, J-M and Ghahramani, Z and Heskes, T (2011) The Dynamic Beamformer. In: UNSPECIFIED pp. 148-155..

Knowles, DA and Gael, JV and Ghahramani, Z (2011) Message Passing Algorithms for the Dirichlet Diffusion Tree. In: UNSPECIFIED pp. 721-728..

Abbott, JT and Heller, KA and Ghahramani, Z and Griffiths, TL (2011) Testing a Bayesian Measure of Representativeness Using a Large Image Database. In: UNSPECIFIED pp. 2321-2329..

Rotsos, C and Van Gael, J and Moore, AW and Ghahramani, Z (2010) Probabilistic graphical models for semi-supervised traffic classification. In: UNSPECIFIED pp. 752-757..

Ghahramani, Z (2010) (Invited Talk) Bayesian Hidden Markov Models and Extensions. In: UNSPECIFIED p. 56..

Stegle, O and Denby, K and McHattie, S and Meade, A and Wild, D and Ghahramani, Z and Borgwardt, K (2009) Discovering temporal patterns of differential gene expression in microarray time series. In: German Conference on Bioinformatics, 2009-9-28 to 2009-9-30, Martin Luther University, Halle-Wittenberg, Germany pp. 133-142..

van Gael, J and Vlachos, A and Ghahramani, Z (2009) The infinite HMM for unsupervised POS tagging. In: EMNLP 2009: Empirical Methods in Natural Language Processing, 2009-8-6 to 2009-8-7, Suntec City, Singapore.

Doshi Velez, F and Ghahramani, Z (2009) Correlated non-parametric latent feature models. In: UAI 2009 (Conference on Uncertainty in Artificial Intelligence), 2009-6-18 to 2009-6-21, Montreal, Quebec.

Doshi Velez, F and Ghahramani, Z (2009) Accelerated Gibbs sampling for the Indian buffet process. In: The 26th International Conference On Machine Learning, ICML 2009, 2009-6-14 to 2009-6-18, Montreal Quebec, Canada pp. 273-280..

Adams, R and Ghahramani, Z (2009) Archipelago: nonparametric bayesian semi-supervised learning. In: International Conference on Machine Learning, ICML 2009, 2009-6-14 to 2009-6-18, Montreal Quebec, Canada pp. 1-8..

Stegle, O and Denby, K and Wild, DL and Ghahramani, Z (2009) A robust bayesian two-sample test for detecting intervals of differential gene expression in microarray time series. In: 13th Annual International Conference on Research in Computational Molecular Biology, RECOMB 2009, 2009-5-18 to 2009-5-21, Tucson, Arizona.

Vlachos, A and Korhonen, A and Ghahramani, Z (2009) Unsupervised and constrained dirichlet process mixture models for verb clustering. In: 4th Workshop on Statistical Machine Translation, EACL' 09, 2009-3-30 to 2009-4-3, Athens, Greece.

Eaton, F and Ghahramani, Z (2009) Choosing a variable to clamp: approximate inference using conditioned belief propagation. In: AISTATS Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS) 2009, 2009-4-16 to 2009-4-18, Florida, USA pp. 145-152..

Silva, R and Ghahramani, Z (2009) Factorial mixture of gaussians and the marginal independence model. In: Twelfth International Conference on Artificial Intelligence and Statistics, AISTATS 09, 2009-4-16 to 2009-4-18, Florida, USA pp. 520-527..

Chu, W and Ghahramani, Z (2009) Probabilistic models for incomplete multi-dimensional arrays. In: AISTATS Twelfth International Conference on Artificial Intelligence and Statistics 2009, 2009-4-16 to 2009-4-18, Florida, USA pp. 89-96..

Xu, Y and Heller, KA and Ghahramani, Z (2009) Tree-based inference for dirichlet process mixtures. In: AISTATS Proceedings of the 12th International Conference on Artificial Intelligence and Statistics (AISTATS)2009, 2009-4-16 to 2009-4-18, Florida USA pp. 623-630..

Stepleton, T and Ghahramani, Z and Gordon, G and Lee, TS (2009) The block diagonal infinite hidden markov model. In: AISTATS Twelfth International Conference on Artificial Intelligence and Statistics 2009, 2009-4-16 to 2009-4-18, Florida, USA pp. 552-559..

Lippert, C and Stegle, O and Ghahramani, Z and Borgwardt, K (2009) A kernel method for unsupervised structured network inference. In: JMLR: Workshop and Conference Proceedings Vol.5: 12th International Conference on Artificial Intelligence and Statistics, AISTATS 2009, 2009-4-16 to 2009-4-18, Florida, USA pp. 368-375..

Mohamed, S and Doshi Velez, F and Knowles, D and Ghahramani, Z (2009) Large scale nonparametric Bayesian inference:data parallelisation an the Indian buffet process. In: NIPS 2009 Neural Information Processing Systems Conference, 2009-12-7 to 2009-12-12, Vancouver, Canada.

Doshi-Velez, F and Ghahramani, Z (2009) Accelerated sampling for the Indian Buffet Process. In: UNSPECIFIED pp. 273-280..

Doshi-Velez, F and Ghahramani, Z (2009) Correlated Non-Parametric Latent Feature Models. In: UNSPECIFIED pp. 143-150..

Stegle, O and Denby, K and Wild, DL and Ghahramani, Z and Borgwardt, KM (2009) A Robust Bayesian Two-Sample Test for Detecting Intervals of Differential Gene Expression in Microarray Time Series. In: UNSPECIFIED pp. 201-216..

Vlachos, A and Ghahramani, Z and Korhonen, A (2008) Dirichlet process mixture models for verb clustering. In: Workshop on Prior Knowledge for Text and Language Processing, 2008-7-9 to --, Helsinki, Finland.

van Gael, J and Saatci, Y and Teh, YW and Ghahramani, Z (2008) Beam sampling for the infinite hidden markov model. In: 25th International Conference on Machine Learning, 2008-7-5 to 2008-7-9, Helsinki, Finland pp. 1088-1095..

Heller, KA and Williamson, SA and Ghahramani, Z (2008) Statistical models for partial membership. In: 25th International Conference on Machine Learning, 2008-7-5 to 2008-7-9, Helsinki, Finland pp. 329-339..

Kim, H and Ghahramani, Z (2008) Outlier robust gaussian process classification. In: 7th International Workshop on Statistical Pattern Recognition, SPR' 08, 2008-- to --, Orlando, USA pp. 896-905..

Huebler, C and Borgwardt, K and Kriegel, HP and Ghahramani, Z (2008) Metropolis algorithms for representative subgraph sampling. In: 8th IEEE International Conference on Data Mining, ICDM' 08, 2008-12-15 to 2008-12-19, Pisa, Italy pp. 283-292..

Williamson, S and Ghahramani, Z (2008) Probabilistic models for data combination in recommender systems. In: Learning from Multiple Sources Workshop, 2008-12-8 to 2008-12-12, Vancouver and Whistler, British Columbia, Canada.

van Gael, J and Teh, YW and Ghahramani, Z (2008) The infinite factorial hidden markov model. In: 22nd Annual Conference on Neural Information Processing Systems, NIPS 2008, 2008-12-8 to 2008-12-12, Vancouver and Whistler, British Columbia, Canada -..

Mohamed, S and Heller, KA and Ghahramani, Z (2008) Bayesian exponential family PCA. In: NIPS 2009 Neural Information Processing Systems Conference, 2008-12-8 to 2008-12-10, Vancouver, Canada -..

Mohamed, S and Heller, KA and Ghahramani, Z (2008) Bayesian Exponential Family PCA. In: UNSPECIFIED pp. 1089-1096..

Ghahramani, Z (2008) Bayesian Methods for Artificial Intelligence and Machine Learning. In: UNSPECIFIED p. 8..

Gael, JV and Teh, YW and Ghahramani, Z (2008) The Infinite Factorial Hidden Markov Model. In: UNSPECIFIED pp. 1697-1704..

Heller, KA and Williamson, S and Ghahramani, Z (2008) Statistical models for partial membership. In: UNSPECIFIED pp. 392-399..

Silva, R and Heller, KA and Ghahramani, Z (2007) Analogical reasoning with relational Bayesian sets. In: 11th International Conference on Artifical Intelligence and Statistics (AISTATS), 2007-3- to --, San Juan, PR, US.

Chu, W and Ghahramani, Z and Krause, R and Wild, DL (2007) Identifying protein complexes from high-throughput protein interaction screens. In: 17th Annual Mathematical and Statistical Aspects of Molecular Biology Workshop, 2007-3- to --, Manchester, UK.

Knowles, D and Ghahramani, Z (2007) Infinite sparse factor analysis and infinite independent components analysis. In: 7th International Conference on Independent Component Analysis and Signal Separation (ICA 2007), 2007-9- to --, London, UK pp. 381-388..

Snelson, E and Ghahramani, Z (2007) Local and global sparse Gaussian process approximations. In: 11th International Conference on Artifical Intelligence and Statistics (AISTATS), 2007-3- to --, San Juan, PR, US.

Teh, YW and Ghahramani, Z (2007) Stick-breaking construction for the Indian buffet. In: 11th International Conference on Artifical Intelligence and Statistics (AISTATS), 2007-3- to --, San Juan, PR, US.

Heller, KA and Ghahramani, Z (2007) A nonparametric Bayesian approach to modeling overlapping clusters. In: Eleventh International Conference on Artifical Intelligence and Statistics (AISTATS), 2007-3- to --, San Juan, PR, US.

Silva, R and Chu, W and Ghahramani, Z (2007) Hidden common cause relations in relational learning. In: 21st Annual Conference on Neural Information Processing Systems, 2007-12-3 to 2007-12-6, Vancouver, Canada -..

(2007) Machine Learning, Proceedings of the Twenty-Fourth International Conference (ICML 2007), Corvallis, Oregon, USA, June 20-24, 2007. In: UNSPECIFIED.

Azran, A and Ghahramani, Z (2006) A new approach to data driven clustering. In: The 23rd International Conference on Machine learning; ICML 2006, 2006-8- to --, Pittsburgh, PA, US pp. 57-64..

Kim, HC and Kim, D and Ghahramani, Z and Bang, SY (2006) Gender classification with Bayesian kernel methods. In: 2006 International Joint Conference on Neural Networks (IJCNN), 2006-7-16 to 2006-7-21, Vancouver, BC, Canada.

Silva, R and Ghahramani, Z (2006) Bayesian inference for Gaussian mixed graph models. In: 22nd Conference on Uncertainty in Artificial Intelligence (UAI 2006), 2006-7-13 to 2006-7-16, Cambridge, MA, US pp. 453-460..

Murray, IA and Ghahramani, Z and MacKay, DJC (2006) MCMC for doubly-intractable distributions. In: 22nd Conference on Uncertainty in Artificial Intelligence (UAI 2006), 2006-7-13 to 2006-7-16, Cambridge, MA, US pp. 359-366..

Snelson, E and Ghahramani, Z (2006) Variable noise and dimensionality reduction for sparse Gaussian processes. In: UAI 2006: 22nd Conference on Uncertainty in Artificial Intelligence, 2006-7-13 to 2006-7-16, Cambridge, MA, US pp. 461-468..

Wood, F and Griffiths, TL and Ghahramani, Z (2006) A non-parametric Bayesian method for inferring hidden causes. In: 22nd Conference on Uncertainty in Artificial Intelligence (UAI 2006), 2006-7-13 to 2006-7-16, Cambridge, MA, US pp. 536-543..

Heller, KA and Ghahramani, Z (2006) A Bayesian approach to information retrieval from sets of items. In: 26th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering CNRS, 2006-7-8 to 2006-7-13, Paris, France.

Ghahramani, Z and Griffiths, TL and Sollich, P (2006) Bayesian nonparametric latent feature models (with discussion). In: 8th Valencia International Meeting on Bayesian Statistics, 2006-6-2 to 2006-6-6, Benidorm, Alicante, Spain -..

Heller, KA and Ghahramani, Z (2006) Efficient Bayesian hierarchical clustering for gene expression data. In: Valencia/ISBA 8th World Meeting on Bayesian Statistics, 2006-6-1 to 2006-6-6, Benidorm, Spain.

Murray, I and Ghahramani, Z and MacKay, DJC (2006) MCMC parameter learning in spatial statistics. In: Valencia/ISBA 8th World Meeting on Bayesian Statistics, 2006-6-1 to 2006-6-6, Benidorm, Spain.

Azran, A and Ghahramani, Z (2006) Spectral methods for automatic multiscale data clustering. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006-6-17 to 2006-6-22, New York, US -..

Heller, KA and Ghahramani, Z (2006) A simple Bayesian framework for content-based image retrieval. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 2006-6-17 to 2006-6-22, New York, US -..

Kurata, D and Nankaku, Y and Tokuda, K and Kitamura, T and Ghahramani, Z (2006) Face recognition based on separate lattice HMMs. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), 2006-5-14 to 2006-5-19, Toulouse, France.

Meeds, E and Ghahramani, Z and Neal, R and Roweis, ST (2006) Modelling dyadic data with binary latent factors. In: 20th Conference on Advances in Neural Information Processing Systems (NIPS), 2006-12-4 to 2006-12-7, Vancouver, Canada pp. 977-984..

Chu, W and Sindhwani, V and Keerthi, S and Ghahramani, Z (2006) Relational learning with Gaussian processes. In: 20th Conference on Advances in Neural Information Processing Systems (NIPS), 2006-12-4 to 2006-12-7, Vancouver, Canada pp. 289-296..

Chu, W and Ghahramani, Z and Krause, R and Wild, DL (2006) Identifying protein complexes in high-throughput protein interaction screens using an infinite latent feature model. In: The Pacific Symposium Biocomputing 2006, 2006-1-3 to 2006-1-7, Hawaii, HI, US pp. 231-242..

Kurata, D and Nankaku, Y and Tokuda, K and Kitamura, T and Ghahramani, Z (2006) Face recognition based on separable lattice HMMS. In: UNSPECIFIED 737-+..

Kurata, D and Nankaku, Y and Tokuda, K and Kitamura, T and Ghahramani, Z (2006) Face recognition based on separable lattice HMMS. In: UNSPECIFIED pp. 5595-5598..

Kim, HC and Kim, D and Ghahramani, Z and Bang, SY (2006) Gender classification with Bayesian kernel methods. In: UNSPECIFIED pp. 3371-3376..

Heller, KA and Ghahramani, Z (2006) A Simple Bayesian Framework for Content-Based Image Retrieval. In: UNSPECIFIED pp. 2110-2117..

Azran, A and Ghahramani, Z (2006) Spectral Methods for Automatic Multiscale Data Clustering. In: UNSPECIFIED pp. 190-197..

Heller, KA and Ghahramani, Z (2005) Bayesian hierarchical clustering. In: The 22nd International Conference on Machine Learning: ICML 2005, 2005-8- to --, Bonn, Germany pp. 297-304..

Snelson, E and Ghahramani, Z (2005) Compact approximations to Bayesian predictive distributions. In: The 22nd International Conference on Machine Learning: ICML 2005, 2005-8- to --, Bonn, Germany pp. 841-848..

Chu, W and Ghahramani, Z (2005) Extensions of Gaussian processes for ranking: semi-supervised and active learning. In: The NIPS 2005 Workshop on Learning to Rank, 2005-12-9 to --, Whistler, BC, US pp. 29-34..

Chu, W and Ghahramani, Z (2005) Preference learning with Gaussian processes. In: The 22nd International Conference on Machine Learning: ICML 2005, 2005-8- to --, Bonn, Germany pp. 137-144..

Sung, JM and Bang, SY and Kim, S and Ghahramani, Z (2005) U-likelihood and U-updating algorithm: statistical inference on latent variable models. In: The 16th European Conference on Machine Learning, 2005-10- to --, Porto, Portugal pp. 377-388..

Heller, KA and Ghahramani, Z (2005) Randomized algorithms for fast Bayesian hierarchical clustering. In: EU-PASCAL Statistics and Optimization of Clustering Workshop, 2005-7-5 to 2005-7-6, London, UK.

Snelson, E and Ghahramani, Z (2005) Compact approximations to Bayesian predictive distributions. In: UNSPECIFIED pp. 840-847..

(2005) Proceedings of the Tenth International Workshop on Artificial Intelligence and Statistics, AISTATS 2005, Bridgetown, Barbados, January 6-8, 2005. In: UNSPECIFIED.

Todorov, E and Ghahramani, Z (2004) Analysis of the synergies underlying complex hand manipulation. In: The 26th IEEE Annual International Conference on Engineering in Medicine and Biology Society; EMBC 2004 - Volume 6, 2004-9- to --, San Francisco, CA, US pp. 4637-4640..

Qi, Y and Minka, TP and Picard, RW and Ghahramani, Z (2004) Predictive automatic relevance determination by expectation propagation. In: The 21st International Conference on Machine Learning: ICML 2004, 2004-7- to --, Banff, AB, Canada pp. 671-678..

Snelson, E and Rasmussen, CE and Ghahramani, Z (2004) Warped Gaussian processes. In: Neural Information Processing Systems, NIPS, 17th Annual Conference, 2003-12- to --, British Columbia, Canada pp. 337-344..

Chu, W and Ghahramani, Z and Wild, DL (2004) A graphical model for protein secondary structure prediction. In: The 21st International Conference on Machine Learning: ICML 2004, 2004-7- to --, Banff, AB, Canada pp. 161-168..

Beal, MJ and Rangel, C and Falciani, F and Ghahramani, Z and Wild, DL (2004) Classical and Bayesian approaches to reconstructing genetic regulatory networks. In: 12th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2004-7-31 to 2004-8-1, Glasgow, UK.

Murray, I and Ghahramani, Z (2004) Bayesian learning in undirected graphical models: approximate MCMC algorithms. In: The 20th Conference on Uncertainty in Artificial Intelligence, 2004-7-7 to 2004-7-11, Banff, AB, Canada pp. 392-399..

Chu, W and Ghahramani, Z and Wild, DL (2004) Secondary structure prediction using Sigmoid belief networks to parameterize segmental semi-Markov models. In: The 12th European Symposium on Artificial Neural Networks (ESANN), 2004-4-28 to 2004-4-30, Bruges, Belgium -..

Dubey, A and Hwang, S and Rangel, C and Rasmussen, CE and Ghahramani, Z and Wild, DL (2004) Clustering protein sequence and structure space with infinite Gaussian mixture models. In: The Pacific Symposium on Biocomputing 2004, 2004-1-6 to 2004-1-10, Hawaii, HI, US pp. 399-410..

Bourne, PE and Allerston, CKJ and Krebs, W and Li, W and Shinyalov, IN and Godzik, A and Friedberg, I and Liu, T and Wild, DL and Hwang, S and Ghahramani, Z and Chen, L and Westbrook, J (2004) The status of structural genomics defined through the analysis of current targets and structures. In: The Pacific Symposium on Biocomputing 2004, 2004-1-6 to 2004-1-10, Hawaii, HI, US pp. 375-386..

Qi, YA and Minka, TP and Picard, RW and Ghahramani, Z (2004) Predictive automatic relevance determination by expectation propagation. In: UNSPECIFIED.

Chu, W and Ghahramani, Z and Wild, DL (2004) Protein secondary structure prediction using sigmoid belief networks to parameterize segmental semi-Markov models. In: UNSPECIFIED pp. 81-86..

Chu, W and Ghahramani, Z and Wild, DL (2004) A graphical model for protein secondary structure prediction. In: UNSPECIFIED.

Rasmussen, CE and Ghahramani, Z (2003) Bayesian Monte Carlo. In: 16th Annual Conference on Neural Information Processing Systems, NIPS'02, 2002-12- to --, British Columbia, Canada pp. 505-512..

Xhu, X and Lafferty, J and Ghahramani, Z (2003) Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions. In: The ICML-2003 Workshop on The Continuum from Labeled to Unlabeled Data, 2003-- to --, Washington, DC, US pp. 58-65..

Kim, HC and Ghahramani, Z (2003) The EM-EP algorithm for Gaussian process classification. In: The Workshop on Probabilistic Graphical Models for Classification held at The 14th European Conference on Machine Learning (ECML) and the 7th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), -- to -- pp. 37-48..

Minka, TP and Ghahramani, Z (2003) Expectation propagation for infinite mixtures (Technical Report). In: NIPS'03 Workshop on Nonparametric Bayesian Methods and Infinite Models, 2003-12-13 to --, Whistler, BC Canada.

Salakhutdinov, R and Roweis, S and Ghahramani, Z (2003) On the convergence of bound optimization algorithms. In: The 19th International Conference on Uncertainty in Artificial Intelligence, 2003-8- to --, Acapulco, Mexico pp. 509-516..

Salakhutdinov, R and Roweis, S and Ghahramani, Z (2003) Optimization with EM and expectation-conjugate-gradient. In: The 20th International Conference on Machine Learning (ICML-2003) Volume 2, 2003-8- to --, Washington, DC, US pp. 672-679..

Zhu, X and Ghahramani, Z and Lafferty, J (2003) Semi-supervised learning using Gaussian fields and harmonic functions. In: The 20th International Conference on Machine Learning (ICML-2003) Volume 2, 2003-8- to --, Washington, DC, US pp. 912-919..

Todorov, E and Ghahramani, Z (2003) Unsupervised learning of sensory-motor synergies. In: Society for Neuroscience Conference, 2003-9- to --, Cancun, Mexico pp. 1750-1753..

Beal, MJ and Ghahramani, Z (2003) The variational Bayesian EM algorithm for incomplete data: with application to scoring graphical model structures. In: Bayesian Statistics 7: the Seventh Valencia International Meeting, 2002-6- to --, Tenerife, Spain pp. 453-464..

Thrun, S and Koller, D and Ghahramani, Z and Durrant-Whyte, H and Ng, AY (2003) Simultaneous mapping and localization with sparse extended information filters: Theory and initial results. In: UNSPECIFIED pp. 363-380..

Wild, DL and Rasmussen, CE and Ghahramani, Z and Cregg, J and de la Cruz, BJ and Kan, CC and Scanlon, K (2002) A Bayesian approach to modelling uncertainty in gene expression clusters. In: 3rd International Conference on Systems Biology, 2002-- to --, Stockholm, Sweden.

Rasmussen, CE and Ghahramani, Z (2002) Infinite mixtures of Gaussian process experts. In: Advances in Neural Information Processing Systems 14: the 2001 Neural Information Processing Systems (NIPS) Conference, 2001-- to -- pp. 881-888..

Beal, MJ and Ghahramani, Z and Rasmussen, CE (2002) The infinite hidden Markov model. In: Advances in Neural Information Processing Systems 14: the 2001 Neural Information Processing Systems (NIPS) Conference, 2001-- to --, British Columbia, Canada pp. 577-585..

Rasmussen, CE and Ghahramani, Z (2002) Bayesian Monte Carlo. In: UNSPECIFIED pp. 489-496..

Jin, R and Ghahramani, Z (2002) Learning with Multiple Labels. In: UNSPECIFIED pp. 897-904..

Korenberg, AT and Ghahramani, Z (2001) Adaptative feedback control for non-stationary dynamics. In: 3rd International Conference on Sensorimotor Control in Man and Machines, 2001-- to --, Marseille, France.

Rasmussen, CE and Ghahramani, Z (2001) Occam's razor. In: 14th Annual Conference on Advances on Neural Information Processing Systems, NIPS 2000, 2000-11- to --, Denver, CO, US pp. 294-300..

Korenberg, AT and Ghahramani, Z (2001) Adaptation to switching force fields. In: 11th Annual Meeting of Neural Control of Movement, 2001-3-24 to 2001-4-1, Seville, Spain.

Todorov, E and Ghahramani, Z (2001) A theory of optimal motor-sensory primitives. In: 11th Annual Meeting of Neural Control of Movement, 2001-3-24 to 2001-4-1, Seville, Spain.

Rangel, C and Wild, DL and Falciani, F and Ghahramani, Z (2001) Modelling biological responses using gene expression profiling and linear dynamical systems. In: The 2nd International Conference on Systems Biology: The Future of Biology in the 21st Century (ICSB), 2001-11-4 to 2001-11-7, California, US pp. 248-256..

(2001) Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, NIPS 2001, December 3-8, 2001, Vancouver, British Columbia, Canada]. In: UNSPECIFIED.

Wild, DL and Raval, A and Ghahramani, Z (2000) A Bayesian network model for protein fold and remote homologue recognition. In: 8th International Conference on Intelligent Systems for Molecular Biology (ISMB), 2000-8- to --, La Jolla, CA, US.

Adams, NJ and Storkey, AJ and Ghahramani, Z and Williams, CKI (2000) MFDTs: mean field dynamic trees. In: The 15th International Conference on Pattern Recognition v.3, 2000-9- to --, Barcelona, Spain pp. 147-150..

Ueda, N and Ghahramani, Z (2000) Optimal model inference for Bayesian mixture of experts. In: The 2000 IEEE Signal Processing Society Workshop on Neural Networks for Signal Processing X v.1, 2000-12- to --, Sydney, Australia pp. 145-151..

Hamilton, AF and Jones, KE and Ghahramani, Z and Lemon, RN and Wolpert, DM (2000) The coding of movements in primary motor cortex: a TMS study. In: ICN-ISC Meeting, 2000-- to --, Lyons, France.

Todorov, E and Ghahramani, Z (2000) Degrees of freedom and hand synergies in manipulation tasks. In: 10th Annual Meeting on the Neural Control of Movement, 2000-4-9 to 2000-4-14, Key West, FL, US.

Vetter, P and Ghahramani, Z and Kawato, M and Wolpert, DM (2000) Multiple linear controllers for nonlinear and nonstationary dynamics. In: 10th Annual Meeting on the Neural Control of Movement, 2000-4-9 to 2000-4-14, Key West, FL, US.

Adams, NJ and Storkey, AJ and Williams, CKI and Ghahramani, Z (2000) MFDTs: Mean Field Dynamic Trees. In: UNSPECIFIED pp. 3151-3154..

Ueda, N and Nakano, R and Ghahramani, Z and Hinton, GE (1999) Pattern classification using a mixture of factor analyzers. In: The 9th Workshop on Neural Networks for Signal Processing (NNSP'99), 1999-8- to --, Madison, WI, US pp. 525-534..

Ghahramani, Z and Korenberg, A and Hinton, GE (1999) Scaling in a hierarchical unsupervised network. In: The 9th International Conference on Artificial Neural Networks; ICANN 99, 1999-9- to --, Edinburgh, UK pp. 13-18..

Wild, D and Ghahramani, Z (1998) A Bayesian network approach to protein fold recognition. In: 6th International Conference on Intelligent Systems for Molecular Biology (ISMB), 1998-6- to --, Montreal, Canada.

Ueda, N and Nakano, R and Ghahramani, Z and Hinton, GE (1998) Split and merge EM algorithm for improving Gaussian mixture density estimates. In: The 8th Workshop on Neural Networks for Signal Processing, 1998-8- to --, Cambridge, UK pp. 274-283..

Ghahramani, Z and Hinton, GE (1998) Hierarchical non-linear factor analysis and topographic maps. In: UNSPECIFIED pp. 486-492..

Hinton, GE and Sallans, B and Ghahramani, Z (1998) A hierarchical community of experts. In: UNSPECIFIED pp. 479-494..

Ghahramani, Z (1993) Solving inverse problems using an EM approach to density estimation. In: The 1993 Connectionist Models Summer School, 1993-- to --, Boulder, CO, US pp. 316-323..

Ghahramani, Z and Allen, RB (1991) Temporal processing with connectionist networks. In: The International Joint Conference on Neural Networks (IJCNN'91), 1991-11- to --, Seattle, WA, US pp. 541-546..

Lee, J and Heaukulani, C and Ghahramani, Z and James, LF and Choi, S Bayesian inference on random simple graphs with power law degree distributions. In: ICML 2017, 2017-8-6 to 2017-8-11, International Conference Centre, Sydney Australia. (Unpublished)

Balog, M and Tripuraneni, N and Ghahramani, Z and Weller, A Lost Relatives of the Gumbel Trick. In: ICML 2017, 2017-8-6 to 2017-8-11, International Conference Centre, Sydney, Australia. (Unpublished)

Tripuraneni, N and Rowland, M and Ghahramani, Z and Turner, R Magnetic Hamiltonian Monte Carlo. In: ICML 2017, 2017-8-6 to 2017-8-11, International Conference Centre, Sydney Australia. (Unpublished)

Lloyd, JR and Orbanz, P and Ghahramani, Z and Roy, D Random function priors for exchangeable arrays with applications to graphs and relational data. In: Neural Information Processing Systems, 2012-12-3 to 2012-12-10, South Lake Tahoe, Nevada. (Unpublished)

Dziugaite, GK and Roy, DM and Ghahramani, Z Training generative neural networks via Maximum Mean Discrepancy optimization. In: Association for Uncertainty in Artificial Intelligence UAI 2015, 2018-7-13 to 2018-5-15. (Unpublished)

Monograph

Heller, KA and Ghahramani, Z (2006) Bayesian Hierarchical clustering. Technical Report. Gatsby Computational Neuroscience Unit, University College London (UCL), London, UK.

Murray, I and Ghahramani, Z (2006) A note on the evidence and Bayesian Occam's razor. Technical Report. Gatsby Computational Neuroscience Unit, University College London (UCL), London, UK.

Beal, M and Ghahramani, Z (2006) The variational Kalman smoother. Technical Report. Gatsby Computational Neuroscience Unit, University College London (UCL), London, UK.

Griffiths, TL and Ghahramani, Z (2005) Infinite latent feature models and the indian buffet process. Technical Report. Gatsby Computational Neuroscience Unit, University College London (UCL), London, UK.

Zhu, X and Ghahramani, Z and Lafferty, J (2005) Time-sensitive Dirichlet process mixture models. Technical Report. Carnegie Mellon University: School of Computer Science, Pittsburgh PA, USA.

Chu, W and Ghahramani, Z (2004) Gaussian processes for ordinal regression. Technical Report. Gatsby Computational Neuroscience Unit, University College London (UCL), London, UK.

Tuttle, E and Ghahramani, Z (2004) Propagating uncertainty in POMDP value iteration with Gaussian processes. Technical Report. Gatsby Computational Neuroscience Unit, University College London (UCL), London, UK.

Ghahramani, Z and Kim, HC (2003) Bayesian classifier combination. Technical Report. Gatsby Computational Neuroscience Unit, University College London (UCL), London, UK.

Ohno, Y and Nankaku, Y and Tokuda, K and Kitamura, T and Ghahramani, Z (2003) The training algorithm based on variational approximation for separable 2D-HMM. Technical Report. The Institute of Electronics, Information and Communication Engineers (IEICE), Japan.

Salakhutdinov, R and Roweis, S and Ghahramani, Z (2002) Expectation-conjugate gradient: an alternative to EM. Technical Report. University of Toronto: Department of Computer Science, Toronto, Canada.

Zhu, X and Ghahramani, Z (2002) Learning from labels and unlabeled data with label propagation. Technical Report. Carnegie Mellon University: School of Computer Science, Pittsburgh PA, USA.

Zhu, X and Ghahramani, Z and Lafferty, J (2002) Towards semi-supervised classification with Markov random fields. Technical Report. Carnegie Mellon University: School of Computer Science, Pittsburgh PA, USA.

Ghahramani, Z and Hinton, GE (1996) Parameter estimation for linear dynamical systems. Technical Report. University of Toronto: Department of Computer Science, Toronto, Canada.

Rasmussen, CE and Neal, RM and Hinton, GE and Van Camp, D and Revow, M and Ghahramani, Z and Kustra, R and Tibshirani, R (1996) The delve manual. Technical Report. University of Toronto: Department of Computer Science, Toronto, Canada.

Ghahramani, Z and Hinton, GE (1996) The EM algorithm for mixtures of factor analyzers. Technical Report. University of Toronto: Department of Computer Science, Toronto, Canada.

Thesis

Ghahramani, Z (1995) Computation and psychophysics of sensorimotor integration. PhD thesis, UNSPECIFIED.

Ghahramani, Z (1990) A neural network for learning how to parse tree adjoining grammars. Other thesis, UNSPECIFIED.

This list was generated on Thu Oct 17 17:28:24 2019 BST.