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George Tucker

1987–2025 年に発表

58
論文数
30,247
被引用数
40
h 指数
52
i10 指数

被引用数

George Tucker の年別被引用数1981 年: 被引用 1 件1994 年: 被引用 1 件1995 年: 被引用 3 件1996 年: 被引用 1 件1997 年: 被引用 1 件1998 年: 被引用 2 件1999 年: 被引用 4 件2000 年: 被引用 2 件2001 年: 被引用 9 件2002 年: 被引用 5 件2003 年: 被引用 2 件2004 年: 被引用 5 件2005 年: 被引用 3 件2006 年: 被引用 1 件2007 年: 被引用 1 件2008 年: 被引用 3 件2009 年: 被引用 3 件2010 年: 被引用 2 件2011 年: 被引用 5 件2012 年: 被引用 7 件2013 年: 被引用 10 件2014 年: 被引用 9 件2015 年: 被引用 38 件2016 年: 被引用 71 件2017 年: 被引用 95 件2018 年: 被引用 221 件2019 年: 被引用 509 件2020 年: 被引用 886 件2021 年: 被引用 1,570 件2022 年: 被引用 1,596 件2023 年: 被引用 1,886 件2024 年: 被引用 4,465 件2025 年: 被引用 6,459 件2026 年: 被引用 2,694 件2027 年: 被引用 1 件1982〜1993 年は被引用が無いため表示していません

引用元

国・地域

この著者を引用した国・地域の世界地図アメリカ合衆国: 引用元論文 3,346 件、この内訳の 25.3%中国: 引用元論文 2,281 件、この内訳の 17.2%イギリス: 引用元論文 1,119 件、この内訳の 8.5%ドイツ: 引用元論文 629 件、この内訳の 4.8%カナダ: 引用元論文 575 件、この内訳の 4.4%オーストラリア: 引用元論文 402 件、この内訳の 3%韓国: 引用元論文 366 件、この内訳の 2.8%日本: 引用元論文 326 件、この内訳の 2.5%オランダ: 引用元論文 307 件、この内訳の 2.3%香港: 引用元論文 284 件、この内訳の 2.1%フランス: 引用元論文 282 件、この内訳の 2.1%シンガポール: 引用元論文 270 件、この内訳の 2%
0%25.3%その他 23%

機関

分野

  • Computer Science67.3%
  • Engineering9.7%
  • Biochemistry, Genetics and Molecular Biology6.4%
  • Medicine3.4%
  • Decision Sciences2.7%
  • Social Sciences2.6%
  • その他7.9%

トピック

  • 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%
  • その他72.3%

共著者

全論文

検索で開く
  1. Gemini: A Family of Highly Capable Multimodal Models

    著者: 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 ほか 1,251 名 - arXiv (Cornell University), CoRR 2023 被引用: 6,876

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

    著者: 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 ほか 8 名 - arXiv (Cornell University), CoRR 2024 被引用: 2,238

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

    著者: Sergey Levine, Aviral Kumar, George Tucker, Justin Fu - arXiv (Cornell University), CoRR 2020 被引用: 1,955

  4. Soft Actor-Critic Algorithms and Applications

    著者: 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 被引用: 2,198

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

    著者: Justin Fu, Aviral Kumar, Ofir Nachum, George Tucker, Sergey Levine - arXiv (Cornell University), CoRR 2020 被引用: 1,177

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

    著者: 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 被引用: 430

  7. Behavior Regularized Offline Reinforcement Learning

    著者: Yifan Wu, George Tucker, Ofir Nachum - arXiv (Cornell University), CoRR 2019 被引用: 655

  8. Conservative Q-Learning for Offline Reinforcement Learning

    著者: Aviral Kumar, Aurick Zhou, George Tucker, Sergey Levine - NeurIPS 2020 被引用: 2,694

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

    著者: 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 被引用: 1,789

  10. Model Based Reinforcement Learning for Atari

    著者: 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 被引用: 996

  11. Regularizing Neural Networks by Penalizing Confident Output Distributions

    著者: Gabriel Pereyra, George Tucker, Jan Chorowski, Lukasz Kaiser, Geoffrey E. Hinton - ICLR (Workshop) 2017 被引用: 1,267

  12. Learning to Walk Via Deep Reinforcement Learning

    著者: Tuomas Haarnoja, Sehoon Ha, Aurick Zhou, Jie Tan, George Tucker, Sergey Levine - Robotics: Science and Systems XV 2019 被引用: 436

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

    著者: Aviral Kumar, Justin Fu, Matthew Soh, George Tucker, Sergey Levine - NeurIPS 2019 被引用: 1,323

  14. Widespread Macromolecular Interaction Perturbations in Human Genetic Disorders

    著者: 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 被引用: 650

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

    著者: 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 被引用: 215

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

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

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

    著者: Carlos Riquelme, George Tucker, Jasper Snoek - ICLR (Poster) 2018 被引用: 394

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

    著者: Yifan Wu, George Tucker, Ofir Nachum - ICLR (Poster) 2019 被引用: 119

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

    著者: Aviral Kumar, Rishabh Agarwal, Xinyang Geng, George Tucker, Sergey Levine - ICLR 2023 被引用: 80

  20. Benchmarks for Deep Off-Policy Evaluation

    著者: 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 被引用: 117

  21. On Variational Bounds of Mutual Information

    著者: Ben Poole, Sherjil Ozair, Aäron van den Oord, Alexander A. Alemi, George Tucker - ICML 2019 被引用: 1,040

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

    著者: 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 被引用: 63

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

    著者: Aviral Kumar, Rishabh Agarwal, Tengyu Ma, Aaron C. Courville, George Tucker, Sergey Levine - ICLR 2022 被引用: 89

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

    著者: Jacob Buckman, Danijar Hafner, George Tucker, Eugene Brevdo, Honglak Lee - Neural Information Processing Systems, NeurIPS 2018 被引用: 370