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
Riemannian continuous normalizing flows
E Mathieu, M Nickel
arXiv preprint arXiv:2006.10605, 2020
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
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
A dynamic simulation model to support reduction in illegal trade within legal wildlife markets
R Oyanedel, S Gelcich, E Mathieu, EJ Milner‐Gulland
Conservation Biology, 2021
InteL-VAEs: Adding Inductive Biases to Variational Auto-Encoders via Intermediary Latents
N Miao, E Mathieu, N Siddharth, YW Teh, T Rainforth
arXiv preprint arXiv:2106.13746, 2021
On Contrastive Representations of Stochastic Processes
E Mathieu, A Foster, YW Teh
arXiv preprint arXiv:2106.10052, 2021
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 1–14