Richards, B.A., Lillicrap, T.P., Beaudoin, P., Bengio, Y., Bogacz, R., Christensen, A., ...Ganguli, S. (2019). A deep learning framework for neuroscience..Nat Neurosci, 22 (11), 1761-1770. doi:10.1038/s41593-019-0520-2
Richards, B.A., Lillicrap, T.P., Beaudoin, P., Bengio, Y., Bogacz, R., Christensen, A., ...Ganguli, S. (2019). A deep learning framework for neuroscience..Nat Neurosci, 22 (11), 1761-1770. doi:10.1038/s41593-019-0520-2
Saxe, A.M., Bansal, Y., Dapello, J., Advani, M., Kolchinsky, A., Tracey, B.D., Cox, D.D. (2019). On the information bottleneck theory of deep learning.Journal of Statistical Mechanics: Theory and Experiment, 124020. doi:10.1088/1742-5468/ab3985
Adorisio, M., Pezzotta, A., de Mulatier, C., Micheletti, C., Celani, A. (2018). Exact and Efficient Sampling of Conditioned Walks.Journal of Statistical Physics, 170 (1), 79-100. doi:10.1007/s10955-017-1911-y
Orbanz, P., Teh, Y.W. (2017). Bayesian Nonparametric Models. In Encyclopedia of Machine Learning and Data Mining. (pp. 107-116). Springer US.
Bang, D., Aitchison, L., Moran, R., Herce Castanon, S., Rafiee, B., Mahmoodi, A., ...Summerfield, C. (2017). Confidence matching in group decision-making.Nature Human Behaviour, 1 (6), 0117. doi:10.1038/s41562-017-0117
Navajas, J., Hindocha, C., Foda, H., Keramati, M., Latham, P.E., Bahrami, B. (2017). The idiosyncratic nature of confidence.Nature Human Behaviour, doi:10.1038/s41562-017-0215-1
Muandet, K., Sriperumbudur, B., Fukumizu, K., Gretton, A., Schoelkopf, B. (2016). Kernel Mean Shrinkage Estimators.Journal of Machine Learning Research, 17 1-41.
Gallistel, C.R., Krishan, M., Liu, Y., Miller, R., Latham, P.E. (2014). The perception of probability..PSYCHOLOGICAL REVIEW, 121 (1), 96-123. doi:10.1037/a0035232
Sahani, M., Williamson, R.S., Ahrens, M.B., Linden, J.F. (2013). Probabilistic methods for linear and multilinear models.. In Depireux, D.A., Elhilali, M. (Eds.), Handbook of Modern Techniques in Auditory Cortex. (pp. 193-222). Nova Science Pub Incorporated.
Grünewälder, S., Gretton, A., Shawe-Taylor, J. (2013). Smooth operators.30th International Conference on Machine Learning, ICML 2013, (PART 3), 2221-2229.
Grünewälder, S., Lever, G., Baldassarre, L., Patterson, S., Gretton, A., Pontil, M. (2012). Conditional mean embeddings as regressors.Proceedings of the 29th International Conference on Machine Learning, ICML 2012, 2 1823-1830.
Turner, R.E., Sahani, M. (2011). Demodulation as Probabilistic Inference.IEEE Transactions on Audio, Speech and Language Processing, 19 (8), 2398-2411. doi:10.1109/TASL.2011.2135852
Jacobs, A.L., Fridman, G., Douglas, R.M., Alam, N.M., Latham, P.E., Prusky, G.T., Nirenberg, S. (2009). Ruling out and ruling in neural codes.PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 106 (14), 5936-5941. doi:10.1073/pnas.0900573106
Gretton, A., Fukumizu, K., Teo, C.H., Song, L., Schoelkopf, B., Smola, A. (2008). A Kernel Statistical Test of Independence. In Platt, J.C., Koller, D., Singer, Y., Roweis, S. (Eds.), Advances in Neural Information Processing Systems 20. Cambridge, MA: MIT Press.
Song, L., Smola, A., Borgwardt, K., Gretton, A. (2008). Colored Maximum Variance Unfolding. In Platt, J.C., Koller, D., Singer, Y., Roweis, S. (Eds.), Advances in Neural Information Processing Systems 20. Cambridge, MA: MIT Press.
Gretton, A., Borgwardt, K., Rasch, M., Schoelkopf, B., Smola, A. (2007). A Kernel Approach to Comparing Distributions. In Holte, R., Howe, A. (Eds.), Proceedings of the 22nd AAAI Conference on Artificial Intelligence. (p. 1637-1641). AAAI Press.
Gretton, A., Borgwardt, K., Rasch, M., Schoelkopf, B., Smola, A. (2007). A Kernel Method for the Two-Sample-Problem. In Schoelkopf, B., Platt, J., Hoffman, T. (Eds.), Advances in Neural Information Processing Systems 19. (pp. 513-520). Cambridge, MA: MIT Press.
Huang, J., Smola, A., Gretton, A., Borgwardt, K., Schoelkopf, B. (2007). Correcting Sample Selection Bias by Unlabeled Data. In Schoelkopf, B., Platt, J., Hoffman, T. (Eds.), Advances in Neural Information Processing Systems 19. (pp. 601-608). Cambridge, MA: MIT Press.
Latham, P., Pouget, A. (2006). Computing with population codes. In Doya, K., Ishii, S., Pouget, A., Rao, R. (Eds.), Bayesian Brain. Csmbridge: MIT Press.
Sahani, M., Linden, J.F. (2003). How linear are auditory cortical responses?. In Becker, S., Thrun, S., Obermayer, K. (Eds.), Advances in Neural Information Processing Systems. (pp. 301-308). Cambridge, MA, USA: MIT Press.
Park, G., Granatstein, V., Latham, P., Armstrong, C., Ganguly, A., Park, S. (1991). Phase stability of gyroklystron amplifier.IEEE Transactions on Plasma Science, 19 632-640.
Jitkrittum, W., Szabo, Z., Chwialkowski, K., Gretton, A. (1900). Distinguishing distributions with interpretable features. Presented at: International Conference on Machine Learning (ICML): Data-Efficient Machine Learning workshop New York, USA.
Jitkrittum, W., Gretton, A.L., Heess, N., Eslami, S.M.A., Lakshminarayanan, B., Sejdinovic, D., Szabó, Z. (1900). Kernel-Based Just-In-Time Learning For Passing Expectation Propagation Messages. Presented at: International Conference on Machine Learning (ICML) - Large-Scale Kernel Learning: Challenges and New Opportunities workshop Lille, France.