Stebėti
Chris J. Maddison
Pavadinimas
Cituota
Cituota
Metai
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
218702016
The concrete distribution: A continuous relaxation of discrete random variables
CJ Maddison, A Mnih, YW Teh
ICLR, 2017
30292017
Conditional neural processes
M Garnelo, D Rosenbaum, CJ Maddison, T Ramalho, D Saxton, ...
ICML, 2018
8732018
A* sampling
CJ Maddison, D Tarlow, T Minka
NeurIPS, Outstanding Paper Award, 2014
4402014
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
4192019
Rebar: Low-variance, unbiased gradient estimates for discrete latent variable models
G Tucker, A Mnih, CJ Maddison, J Lawson, J Sohl-Dickstein
NeurIPS, 2017
3702017
Filtering variational objectives
CJ Maddison, J Lawson, G Tucker, N Heess, M Norouzi, A Mnih, A Doucet, ...
NeurIPS, 2017
2582017
Tighter variational bounds are not necessarily better
T Rainforth, AR Kosiorek, TA Le, CJ Maddison, M Igl, F Wood, YW Teh
ICML, 2018
2392018
Continuous Hierarchical Representations with Poincaré Variational Auto-Encoders
E Mathieu, CL Lan, CJ Maddison, R Tomioka, YW Teh
NeurIPS, 2019
2112019
Structured generative models of natural source code
CJ Maddison, D Tarlow
ICML, 2014
1972014
Move Evaluation in Go Using Deep Convolutional Neural Networks
CJ Maddison, A Huang, I Sutskever, D Silver
ICLR, 2015
1912015
Doubly reparameterized gradient estimators for Monte Carlo objectives
G Tucker, D Lawson, S Gu, CJ Maddison
ICLR, 2018
1302018
Oops I Took A Gradient: Scalable Sampling for Discrete Distributions
W Grathwohl, K Swersky, M Hashemi, D Duvenaud, CJ Maddison
ICML, 2021
1052021
Identifying the risks of lm agents with an lm-emulated sandbox
Y Ruan, H Dong, A Wang, S Pitis, Y Zhou, J Ba, Y Dubois, CJ Maddison, ...
ICLR, 2024
1002024
Optimal Representations for Covariate Shift
Y Ruan, Y Dubois, CJ Maddison
ICLR, 2022
96*2022
Gradient Estimation with Stochastic Softmax Tricks
MB Paulus, D Choi, D Tarlow, A Krause, CJ Maddison
NeurIPS, 2020
912020
Learning to cut by looking ahead: Cutting plane selection via imitation learning
MB Paulus, G Zarpellon, A Krause, L Charlin, C Maddison
ICML, 2022
892022
Lossy Compression for Lossless Prediction
Y Dubois, B Bloem-Reddy, K Ullrich, CJ Maddison
NeurIPS, 2021
862021
Hamiltonian descent methods
CJ Maddison, D Paulin, YW Teh, B O'Donoghue, A Doucet
arXiv preprint arXiv:1809.05042, 2018
782018
Annealing between distributions by averaging moments
RB Grosse, CJ Maddison, RR Salakhutdinov
NeurIPS, 2013
772013
Sistema negali atlikti operacijos. Bandykite vėliau dar kartą.
Straipsniai 1–20