George Tucker
George Tucker
Google Brain
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Efficient Bayesian mixed-model analysis increases association power in large cohorts
PR Loh, G Tucker, BK Bulik-Sullivan, BJ Vilhjalmsson, HK Finucane, ...
Nature genetics 47 (3), 284-290, 2015
Regularizing neural networks by penalizing confident output distributions
G Pereyra, G Tucker, J Chorowski, Ł Kaiser, G Hinton
arXiv preprint arXiv:1701.06548, 2017
Soft actor-critic algorithms and applications
T Haarnoja, A Zhou, K Hartikainen, G Tucker, S Ha, J Tan, V Kumar, ...
arXiv preprint arXiv:1812.05905, 2018
Widespread macromolecular interaction perturbations in human genetic disorders
N Sahni, S Yi, M Taipale, JIF Bass, J Coulombe-Huntington, F Yang, ...
Cell 161 (3), 647-660, 2015
A quantitative chaperone interaction network reveals the architecture of cellular protein homeostasis pathways
M Taipale, G Tucker, J Peng, I Krykbaeva, ZY Lin, B Larsen, H Choi, ...
Cell 158 (2), 434-448, 2014
Model-based reinforcement learning for atari
L Kaiser, M Babaeizadeh, P Milos, B Osinski, RH Campbell, ...
arXiv preprint arXiv:1903.00374, 2019
On variational bounds of mutual information
B Poole, S Ozair, A Van Den Oord, A Alemi, G Tucker
International Conference on Machine Learning, 5171-5180, 2019
Soft Co-Clustering of Data
FW Elliott, R Rohwer, SC Jones, GJ Tucker, CJ Kain, CN Weidert
US Patent App. 12/133,902, 2009
Rebar: Low-variance, unbiased gradient estimates for discrete latent variable models
G Tucker, A Mnih, CJ Maddison, D Lawson, J Sohl-Dickstein
arXiv preprint arXiv:1703.07370, 2017
Offline reinforcement learning: Tutorial, review, and perspectives on open problems
S Levine, A Kumar, G Tucker, J Fu
arXiv preprint arXiv:2005.01643, 2020
Stabilizing off-policy q-learning via bootstrapping error reduction
A Kumar, J Fu, G Tucker, S Levine
arXiv preprint arXiv:1906.00949, 2019
Sample-efficient reinforcement learning with stochastic ensemble value expansion
J Buckman, D Hafner, G Tucker, E Brevdo, H Lee
arXiv preprint arXiv:1807.01675, 2018
Deep bayesian bandits showdown: An empirical comparison of bayesian deep networks for thompson sampling
C Riquelme, G Tucker, J Snoek
arXiv preprint arXiv:1802.09127, 2018
Learning to walk via deep reinforcement learning
T Haarnoja, S Ha, A Zhou, J Tan, G Tucker, S Levine
arXiv preprint arXiv:1812.11103, 2018
Filtering variational objectives
CJ Maddison, D Lawson, G Tucker, N Heess, M Norouzi, A Mnih, ...
arXiv preprint arXiv:1705.09279, 2017
Methods and devices for ignoring similar audio being received by a system
AD Rosen, MJ Rodehorst, GJ Tucker, ALM Challenner
US Patent 9,728,188, 2017
Proteomic and functional genomic landscape of receptor tyrosine kinase and ras to extracellular signal–regulated kinase signaling
AA Friedman, G Tucker, R Singh, D Yan, A Vinayagam, Y Hu, R Binari, ...
Science signaling 4 (196), rs10-rs10, 2011
Behavior regularized offline reinforcement learning
Y Wu, G Tucker, O Nachum
arXiv preprint arXiv:1911.11361, 2019
Conservative q-learning for offline reinforcement learning
A Kumar, A Zhou, G Tucker, S Levine
arXiv preprint arXiv:2006.04779, 2020
D4rl: Datasets for deep data-driven reinforcement learning
J Fu, A Kumar, O Nachum, G Tucker, S Levine
arXiv preprint arXiv:2004.07219, 2020
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