Chris J. Maddison
Chris J. Maddison
DPhil in Statistics, University of Oxford, DeepMind
Verified email at - Homepage
Cited by
Cited by
Mastering the game of Go with deep neural networks and tree search
D Silver, A Huang, CJ Maddison, A Guez, L Sifre, G Van Den Driessche, ...
Nature 529 (7587), 484, 2016
The concrete distribution: A continuous relaxation of discrete random variables
CJ Maddison, A Mnih, YW Teh
ICLR, 2017
Move Evaluation in Go Using Deep Convolutional Neural Networks
CJ Maddison, A Huang, I Sutskever, D Silver
ICLR, 2015
Rebar: Low-variance, unbiased gradient estimates for discrete latent variable models
G Tucker, A Mnih, CJ Maddison, J Lawson, J Sohl-Dickstein
NeurIPS, 2017
A* sampling
CJ Maddison, D Tarlow, T Minka
NeurIPS, Best Paper Award, 2014
Structured generative models of natural source code
CJ Maddison, D Tarlow
ICML, 2014
Conditional neural processes
M Garnelo, D Rosenbaum, CJ Maddison, T Ramalho, D Saxton, ...
ICML, 2018
Filtering variational objectives
CJ Maddison, J Lawson, G Tucker, N Heess, M Norouzi, A Mnih, A Doucet, ...
NeurIPS, 2017
Tighter variational bounds are not necessarily better
T Rainforth, AR Kosiorek, TA Le, CJ Maddison, M Igl, F Wood, YW Teh
ICML, 2018
Rapid and widespread effects of 17β-estradiol on intracellular signaling in the male songbird brain: a seasonal comparison
SA Heimovics, NH Prior, CJ Maddison, KK Soma
Endocrinology 153 (3), 1364-1376, 2012
Annealing between distributions by averaging moments
RB Grosse, CJ Maddison, RR Salakhutdinov
NeurIPS, 2013
Doubly reparameterized gradient estimators for Monte Carlo objectives
G Tucker, D Lawson, S Gu, CJ Maddison
ICLR, 2018
Soft song during aggressive interactions: seasonal changes and endocrine correlates in song sparrows
CJ Maddison, RC Anderson, NH Prior, MD Taves, KK Soma
Hormones and behavior 62 (4), 455-463, 2012
Hamiltonian descent methods
CJ Maddison, D Paulin, YW Teh, B O'Donoghue, A Doucet
arXiv preprint arXiv:1809.05042, 2018
Particle Value Functions
CJ Maddison, D Lawson, G Tucker, N Heess, A Doucet, A Mnih, YW Teh
Deep Structured Prediction Workshop, ICLR, 2017
Hierarchical Representations with Poincar\'e Variational Auto-Encoders
E Mathieu, CL Lan, CJ Maddison, R Tomioka, YW Teh
NeurIPS, 2019
Twisted variational sequential monte carlo
D Lawson, G Tucker, CA Naesseth, CJ Maddison, RP Adams, YW Teh
Third workshop on Bayesian Deep Learning (NeurIPS), 2018
On Empirical Comparisons of Optimizers for Deep Learning
D Choi, CJ Shallue, Z Nado, J Lee, CJ Maddison, GE Dahl
arXiv preprint arXiv:1910.05446, 2019
Poisson process model for Monte Carlo
CJ Maddison
Perturbation, Optimization, and Statistics, 2016
Direct Policy Gradients: Direct Optimization of Policies in Discrete Action Spaces
G Lorberbom, CJ Maddison, N Heess, T Hazan, D Tarlow
arXiv preprint arXiv:1906.06062, 2019
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