Emile Mathieu
Emile Mathieu
PhD student in Statistics, University of Oxford
Verified email at stats.ox.ac.uk - Homepage
Cited by
Cited by
Disentangling disentanglement in variational autoencoders
E Mathieu, T Rainforth, N Siddharth, YW Teh
International Conference on Machine Learning, 4402-4412, 2019
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
E Mathieu, C Le Lan, CJ Maddison, R Tomioka, YW Teh
Advances in neural information processing systems, 12544-12555, 2019
Sampling and inference for Beta Neutral-to-the-Left models of sparse networks
B Bloem-Reddy, A Foster, E Mathieu, YW Teh
arXiv preprint arXiv:1807.03113, 2018
Riemannian continuous normalizing flows
E Mathieu, M Nickel
Advances in Neural Information Processing Systems 33, 2020
Sampling and inference for discrete random probability measures in probabilistic programs
ZG Benjamin Bloem-Reddy, Emile Mathieu, Adam Foster, Tom Rainforth, Yee Whye ...
NIPS 2017 Workshop on Advances in Approximate Bayesian Inference, 2017
The Turing language for probabilistic programming
ZG Hong Ge, Adam Scibior, Kai Xu, Emile Mathieu, Benjamin Bloem-Reddy, Yee ...
https://github.com/yebai/Turing.jl, 2016
Appendix for Disentangling Disentanglement in Variational Autoencoders
E Mathieu, T Rainforth, N Siddharth, YW Teh
Factorial Hidden Markov Models
E Mathieu
Rapport de Stage Analyse des données de mobilités urbaines
Policy Search Review
E Mathieu, C Reizine
Gaussian Process Bandits
E Mathieu
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Articles 1–11