George Tucker
George Tucker
Google Brain
Verified email at google.com - Homepage
Title
Cited by
Cited by
Year
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, 2015
7692015
Regularizing neural networks by penalizing confident output distributions
G Pereyra, G Tucker, J Chorowski, Ł Kaiser, G Hinton
arXiv preprint arXiv:1701.06548, 2017
4872017
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
3462015
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
3262018
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
2872014
Model-based reinforcement learning for atari
L Kaiser, M Babaeizadeh, P Milos, B Osinski, RH Campbell, ...
arXiv preprint arXiv:1903.00374, 2019
2172019
Soft Co-Clustering of Data
FW Elliott, R Rohwer, SC Jones, GJ Tucker, CJ Kain, CN Weidert
US Patent App. 12/133,902, 2009
2052009
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
1912017
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
159*2019
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
1322018
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
1182018
Filtering variational objectives
CJ Maddison, D Lawson, G Tucker, N Heess, M Norouzi, A Mnih, ...
arXiv preprint arXiv:1705.09279, 2017
1182017
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
992018
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
962017
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
952011
Stabilizing off-policy q-learning via bootstrapping error reduction
A Kumar, J Fu, G Tucker, S Levine
arXiv preprint arXiv:1906.00949, 2019
922019
Network topology and parameter estimation: from experimental design methods to gene regulatory network kinetics using a community based approach
P Meyer, T Cokelaer, D Chandran, KH Kim, PR Loh, G Tucker, M Lipson, ...
BMC systems biology 8 (1), 1-18, 2014
742014
Offline reinforcement learning: Tutorial, review, and perspectives on open problems
S Levine, A Kumar, G Tucker, J Fu
arXiv preprint arXiv:2005.01643, 2020
702020
Max-pooling loss training of long short-term memory networks for small-footprint keyword spotting
M Sun, A Raju, G Tucker, S Panchapagesan, G Fu, A Mandal, ...
2016 IEEE Spoken Language Technology Workshop (SLT), 474-480, 2016
672016
The mirage of action-dependent baselines in reinforcement learning
G Tucker, S Bhupatiraju, S Gu, R Turner, Z Ghahramani, S Levine
International conference on machine learning, 5015-5024, 2018
622018
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Articles 1–20