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Publications

Zhou, Y. et al. (2019) “LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models”, in Proceedings of Machine Learning Research, pp. 148–157.
Mathieu, E. et al. (2019) “Disentangling Disentanglement in Variational Autoencoders”, in Proceedings of Machine Learning Research, pp. 4402–4412.
Fong, E., Lyddon, S. and Holmes, C. (2019) “Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap”, in Proceedings of Machine Learning Research, pp. 1952–1962.
Le, T. et al. (2019) “Revisiting Reweighted Wake-Sleep for Models with Stochastic Control Flow”, in Proceedings of Machine Learning Research, pp. 1039–1049.
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.
Ernst, M., Reinert, G. and Swan, Y. (2018) “Stein-type covariance identities: Klaassen, Papathanasiou and Olkin-Shepp type bounds for arbitrary target distributions”, JournalName [Preprint].
Doherty, A. et al. (2018) “GWAS identifies 14 loci for device-measured physical activity and sleep duration”, Nature Communications, 9.
Lyddon, S., Walker, S. and Holmes, C. (2018) “Nonparametric learning from Bayesian models with randomized objective functions”, in ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), pp. 2071–2081.
Chen, J. et al. (2018) “Stochastic expectation maximization with variance reduction”, in Neural Information Processing Systems. Massachusetts Institute of Technology Press.
Xu, X. and Reinert, G. (2018) “Triad-based comparison and signatures of directed networks”, in Studies in Computational Intelligence. Springer, pp. 590–602.