Emile Mathieu
Emile Mathieu
Postdoctoral Research Associate, University of Cambridge
Verified email at - 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
Advances in Neural Information Processing Systems 33, 2503-2515, 2020
Riemannian score-based generative modeling
V De Bortoli, E Mathieu, M Hutchinson, J Thornton, YW Teh, A Doucet
arXiv preprint arXiv:2202.02763, 2022
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
On contrastive representations of stochastic processes
E Mathieu, A Foster, Y Teh
Advances in Neural Information Processing Systems 34, 28823-28835, 2021
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
On incorporating inductive biases into VAEs
N Miao, E Mathieu, N Siddharth, YW Teh, T Rainforth
International Conference on Learning Representations, 2021
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 36 (2), e13814, 2022
Spectral Diffusion Processes
A Phillips, T Seror, M Hutchinson, V De Bortoli, A Doucet, E Mathieu
arXiv preprint arXiv:2209.14125, 2022
Riemannian Diffusion Schr\" odinger Bridge
J Thornton, M Hutchinson, E Mathieu, V De Bortoli, YW Teh, A Doucet
arXiv preprint arXiv:2207.03024, 2022
Learning Instance-Specific Data Augmentations
N Miao, E Mathieu, Y Dubois, T Rainforth, YW Teh, A Foster, H Kim
arXiv preprint arXiv:2206.00051, 2022
Geometry and representation learning in deep generative models
E Mathieu
University of Oxford, 2021
The Turing language for probabilistic programming
ZG Hong Ge, Adam Scibior, Kai Xu, Emile Mathieu, Benjamin Bloem-Reddy, Yee ..., 2016
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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