Publications

Nalisnick, E. et al. (2019) “Do deep generative models know what they don’t know?”, in 7th International Conference on Learning Representations, ICLR 2019.

Maddison, C., Mnih, A. and Teh, Y. (2019) “The concrete distribution: A continuous relaxation of discrete random variables”, in 5th International Conference on Learning Representations, ICLR 2017 - Conference Track Proceedings.

Mitrovic, J., Sejdinovic, D. and Teh, Y. (2018) “Causal inference via Kernel deviance measures”, in Advances in Neural Information Processing Systems. Massachusetts Institute of Technology Press.

Doherty, A. et al. (2018) “GWAS identifies 14 loci for device-measured physical activity and sleep duration”, Nature Communications, 9.

Chen, J. et al. (2018) “Stochastic expectation maximization with variance reduction”, in Neural Information Processing Systems. Massachusetts Institute of Technology Press.

Miscouridou, X., Caron, F. and Teh, Y. (2018) “Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data”, in Advances in Neural Information Processing Systems 31 (NIPS 2018) pre-proceedings. Neural Information Processing Systems Foundation.

Galashov, A. et al. (2018) “Information asymmetry in KL-regularized RL.”

Wang, Z. et al. (2018) “Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration”, iScience, 9, pp. 451–460.

Martínez-Rubio, D., Kanade, V. and Rebeschini, P. (2018) “Decentralized Cooperative Stochastic Bandits”, arXiv.