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George Tucker

Active 1987–2025

58
Papers
30,247
Citations
40
h-index
52
i10-index

Citations

Citations per year for George Tucker1981: 1 citations1994: 1 citations1995: 3 citations1996: 1 citations1997: 1 citations1998: 2 citations1999: 4 citations2000: 2 citations2001: 9 citations2002: 5 citations2003: 2 citations2004: 5 citations2005: 3 citations2006: 1 citations2007: 1 citations2008: 3 citations2009: 3 citations2010: 2 citations2011: 5 citations2012: 7 citations2013: 10 citations2014: 9 citations2015: 38 citations2016: 71 citations2017: 95 citations2018: 221 citations2019: 509 citations2020: 886 citations2021: 1,570 citations2022: 1,596 citations2023: 1,886 citations2024: 4,465 citations2025: 6,459 citations2026: 2,694 citations2027: 1 citations1982–1993: no citations, so these years are not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 3,346 citing papers, 25.3% of this breakdownChina: 2,281 citing papers, 17.2% of this breakdownUnited Kingdom: 1,119 citing papers, 8.5% of this breakdownGermany: 629 citing papers, 4.8% of this breakdownCanada: 575 citing papers, 4.4% of this breakdownAustralia: 402 citing papers, 3% of this breakdownSouth Korea: 366 citing papers, 2.8% of this breakdownJapan: 326 citing papers, 2.5% of this breakdownNetherlands: 307 citing papers, 2.3% of this breakdownHong Kong: 284 citing papers, 2.1% of this breakdownFrance: 282 citing papers, 2.1% of this breakdownSingapore: 270 citing papers, 2% of this breakdown
0%25.3%Other 23%

Institutions

Fields

  • Computer Science67.3%
  • Engineering9.7%
  • Biochemistry, Genetics and Molecular Biology6.4%
  • Medicine3.4%
  • Decision Sciences2.7%
  • Social Sciences2.6%
  • Other7.9%

Topics

  • Reinforcement Learning in Robotics7.1%
  • Topic Modeling6.5%
  • Multimodal Machine Learning Applications4.9%
  • Natural Language Processing Techniques4%
  • Domain Adaptation and Few-Shot Learning2.7%
  • Adversarial Robustness in Machine Learning2.5%
  • Other72.3%

Coauthors

All papers

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  1. Gemini: A Family of Highly Capable Multimodal Models

    Authors: Gemini Robotics Team, Rohan Anil, Sebastian Borgeaud, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M. Dai, Anja Hauth, Katie Millican, David M. Silver, Melvin Johnson, Ioannis Antonoglou, Julian Schrittwieser, Amelia Glaese, Jilin Chen, Emily Pitler, Timothy Lillicrap, Angeliki Lazaridou, Orhan Fırat, James Molloy, Michael Isard, Paul R. Barham, Tom Hennigan, Benjamin Lee, Fabio Viola, Malcolm Reynolds, Yuanzhong Xu, R. C. Doherty, Eli Collins, Clemens Meyer, Eliza Rutherford, Érica Rodrigues Moreira, Kareem Ayoub, Megha Goel, Jack Krawczyk, Cosmo Du, Ed H., Heng-Tze Cheng, Eric C. Ni, Purvi Shah, Patrick Kane, Betty Chan, Manaal Faruqui, Aliaksei Severyn, Hanzhao Lin, YaGuang Li, Yong Cheng, Abe Ittycheriah, Mahdis Mahdieh, Mia Chen, Pei Sun, Dustin Tran, Sumit Bagri, Balaji Lakshminarayanan, Jeremiah Liu, András Orbán, Fabian Güra, Hao Zhou, Xinying Song, Aurelien Boffy, Harish Ganapathy, Steven Zheng, HyunJeong Choe, Ágoston Weisz, Tao Zhu, Yifeng Lu, Siddharth Gopal, Jarrod Kahn, Maciej Kula, Jeff Pitman, Rushin Shah, Emanuel Taropa, Majd Al Merey, Martin Baeuml, Zhifeng Chen, Laurent El Shafey, Yujing Zhang, Olcan Sercinoglu, George Tucker, Enrique Piqueras, Maxim Krikun, Iain Barr, Nikolay Savinov, Ivo Danihelka, Becca Roelofs, Anaïs White, Anders Andreassen, Tamara von Glehn, Lakshman Yagati, Mehran Kazemi, Lucas Gonzalez, Misha Khalman, Jakub Sygnowski, Alexandre Fréchette, Charlotte G. Smith, Laura Culp, Lev Proleev, Yi Luan, Xi Chen and 1,251 more - arXiv (Cornell University), CoRR 2023 cited by 6,876

  2. Gemma: Open Models Based on Gemini Research and Technology

    Authors: Gemma Team, Thomas Mésnard, Cassidy Hardin, Robert Dadashi, Surya Bhupatiraju, Shreya Pathak, Laurent Sifre, Morgane Rivière, Mihir Kale, Juliette Love, Pouya D. Tafti, Léonard Hussenot, Pier Giuseppe Sessa, Aakanksha Chowdhery, Adam Roberts, Aditya Barua, Alex Botev, Alex Castro-Ros, Ambrose Slone, Amélie Héliou, Andrea Tacchetti, Anna Bulanova, Antonia Paterson, Beth Tsai, Bobak Shahriari, Charline Le Lan, Christopher A. Choquette-Choo, Clément Crepy, Daniel Cer, Daphne Ippolito, David G. Reid, Elena Buchatskaya, Eric C. Ni, Eric Noland, Yan Geng, George Tucker, George-Christian Muraru, Grigory Rozhdestvenskiy, Henryk Michalewski, Ian Tenney, Ivan Grishchenko, Jacob Austin, James Keeling, Jane Labanowski, Jean-Baptiste Lespiau, Jeff Stanway, J. William Brennan, Jeremy J.W. Chen, Johan Ferret, Justin Chiu, Justin Mao-Jones, Katherine Lee, Kathy Yu, Katie Millican, Lars Lowe Sjoesund, Lisa Lee, Lucas Dixon, Machel Reid, Maciej Mikuła, Mateo Wirth, Michael Sharman, Nikolai Chinaev, Nithum Thain, Olivier Bachem, Oscar Chang, Oscar Wahltinez, Paige Bailey, Paul Michel, Petko Yotov, Rahma Chaabouni, Ramona Comanescu, Reena Jana, Rohan Anil, Ross McIlroy, Ruibo Liu, Ryan Mullins, Samuel Smith, Sebastian Borgeaud, Sertan Girgin, Sholto Douglas, Shree Pandya, Siamak Shakeri, Soham De, Ted Klimenko, Tom Hennigan, Vlad Feinberg, Wojciech Stokowiec, Chen, Yu-hui, Zafarali Ahmed, Zhitao Gong, Tris Warkentin, Ludovic Peran, Minh Giang, Clément Farabet, Oriol Vinyals, Jeff Dean, Koray Kavukcuoglu, Demis Hassabis, Zoubin Ghahramani, Douglas Eck and 8 more - arXiv (Cornell University), CoRR 2024 cited by 2,238

  3. Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

    Authors: Sergey Levine, Aviral Kumar, George Tucker, Justin Fu - arXiv (Cornell University), CoRR 2020 cited by 1,955

  4. Soft Actor-Critic Algorithms and Applications

    Authors: Tuomas Haarnoja, Aurick Zhou, Kristian Hartikainen, George Tucker, Sehoon Ha, Jie Tan, Vikash Kumar, Henry Zhu, Abhishek Gupta, Pieter Abbeel, Sergey Levine - arXiv (Cornell University), CoRR 2018 cited by 2,198

  5. D4RL: Datasets for Deep Data-Driven Reinforcement Learning

    Authors: Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine - arXiv (Cornell University), CoRR 2020 cited by 1,177

  6. Training Language Models to Self-Correct via Reinforcement Learning

    Authors: Aviral Kumar, Vincent Zhuang, Rishabh Agarwal, Yi Su, John D. Co-Reyes, Avi Singh, Kate Baumli, Shariq Iqbal, Colton Bishop, Rebecca Roelofs, Lei M. Zhang, Kay McKinney, Disha Shrivastava, Cosmin Paduraru, George Tucker, Doina Precup, Feryal M. P. Behbahani, Aleksandra Faust - ICLR 2025 cited by 430

  7. Behavior Regularized Offline Reinforcement Learning

    Authors: Yifan Wu, George Tucker, Ofir Nachum - arXiv (Cornell University), CoRR 2019 cited by 655

  8. Conservative Q-Learning for Offline Reinforcement Learning

    Authors: Aviral Kumar, Aurick Zhou, George Tucker, Sergey Levine - NeurIPS 2020 cited by 2,694

  9. Efficient Bayesian mixed-model analysis increases association power in large cohorts

    Authors: Po‐Ru Loh, George Tucker, Brendan Bulik‐Sullivan, Bjarni J. Vilhjálmsson, Hilary K. Finucane, Rany M. Salem, Daniel I. Chasman, Paul M. Ridker, Benjamin M. Neale, Bonnie Berger, Nick Patterson, Alkes L. Price - Nature Genetics 2015 cited by 1,789

  10. Model Based Reinforcement Learning for Atari

    Authors: Lukasz Kaiser, Mohammad Babaeizadeh, Piotr Milos, Blazej Osinski, Roy H. Campbell, Konrad Czechowski, Dumitru Erhan, Chelsea Finn, Piotr Kozakowski, Sergey Levine, Afroz Mohiuddin, Ryan Sepassi, George Tucker, Henryk Michalewski - International Conference on Learning Representations, ICLR 2020 cited by 996

  11. Regularizing Neural Networks by Penalizing Confident Output Distributions

    Authors: Gabriel Pereyra, George Tucker, Jan Chorowski, Lukasz Kaiser, Geoffrey E. Hinton - ICLR (Workshop) 2017 cited by 1,267

  12. Learning to Walk Via Deep Reinforcement Learning

    Authors: Tuomas Haarnoja, Sehoon Ha, Aurick Zhou, Jie Tan, George Tucker, Sergey Levine - Robotics: Science and Systems XV 2019 cited by 436

  13. Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction

    Authors: Aviral Kumar, Justin Fu, Matthew Soh, George Tucker, Sergey Levine - NeurIPS 2019 cited by 1,323

  14. Widespread Macromolecular Interaction Perturbations in Human Genetic Disorders

    Authors: Nidhi Sahni, S. Stephen Yi, Mikko Taipale, Juan I. Fuxman Bass, Jasmin Coulombe‐Huntington, Fan Yang, Jian Peng, Jochen Weile, Georgios Ioannis Karras, Yang Wang, I. Kovács, Atanas Kamburov, Irina Krykbaeva, Mandy Hiu Yi Lam, George Tucker, Vikram Khurana, Amitabh Sharma, Yang‐Yu Liu, Nozomu Yachie, Quan Zhong, Yun Shen, Alexandre Palagi, Adriana San‐Miguel, Changyu Fan, Dawit Balcha, Amélie Dricot, Daniel M. Jordan, Jennifer Walsh, Akash Shah, Xinping Yang, Ani K. Stoyanova, Alex Leighton, Michael A. Calderwood, Yves Jacob, Michael E. Cusick, Kourosh Salehi‐Ashtiani, Luke Whitesell, Shamil Sunyaev, Bonnie Berger, Albert-Ĺaszló Barabási, Benoît Charloteaux, David E. Hill, Tong Hao, Frederick P. Roth, Yu Xia, Albertha J.M. Walhout, Susan Lindquist, Marc Vidal - Cell 2015 cited by 650

  15. Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research

    Authors: Cole Gulino, Justin Fu, Wenjie Luo, George Tucker, Eli Bronstein, Yiren Lu, Jean Harb, Xinlei Pan, Yan Wang, Xiangyu Chen, John D. Co-Reyes, Rishabh Agarwal, Rebecca Roelofs, Yao Lu, Nico Montali, Paul Mougin, Zoey Yang, Brandyn White, Aleksandra Faust, Rowan McAllister, Dragomir Anguelov, Benjamin Sapp - NeurIPS 2023 cited by 215

  16. A Quantitative Chaperone Interaction Network Reveals the Architecture of Cellular Protein Homeostasis Pathways

    Authors: Mikko Taipale, George Tucker, Jian Peng, Irina Krykbaeva, Zhen-Yuan Lin, Brett Larsen, Hyungwon Choi, Bonnie Berger, Anne‐Claude Gingras, Susan Lindquist - Cell 2014 cited by 420

  17. Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling

    Authors: Carlos Riquelme, George Tucker, Jasper Snoek - ICLR (Poster) 2018 cited by 394

  18. The Laplacian in RL: Learning Representations with Efficient Approximations

    Authors: Yifan Wu, George Tucker, Ofir Nachum - ICLR (Poster) 2019 cited by 119

  19. Offline Q-Learning on Diverse Multi-Task Data Both Scales And Generalizes

    Authors: Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine - ICLR 2023 cited by 80

  20. Benchmarks for Deep Off-Policy Evaluation

    Authors: Justin Fu, Mohammad Norouzi, Ofir Nachum, George Tucker, Ziyu Wang, Alexander Novikov, Mengjiao Yang, Michael R. Zhang, Yutian Chen, Aviral Kumar, Cosmin Paduraru, Sergey Levine, Tom Le Paine - ICLR 2021 cited by 117

  21. On Variational Bounds of Mutual Information

    Authors: Ben Poole, Sherjil Ozair, Aäron van den Oord, Alexander A. Alemi, George Tucker - ICML 2019 cited by 1,040

  22. Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios

    Authors: Yiren Lu, Justin Fu, George Tucker, Xinlei Pan, Eli Bronstein, Rebecca Roelofs, Benjamin Sapp, Brandyn White, Aleksandra Faust, Shimon Whiteson, Dragomir Anguelov, Sergey Levine - IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2023 cited by 63

  23. DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization

    Authors: Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine - ICLR 2022 cited by 89

  24. Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion

    Authors: Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee - Neural Information Processing Systems, NeurIPS 2018 cited by 370