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Doina Precup

Active 1997–2026

415
Papers
30,279
Citations
62
h-index
215
i10-index

Citations

Citations per year for Doina Precup1960: 1 citations1962: 1 citations1965: 1 citations1974: 1 citations1981: 1 citations1990: 2 citations1995: 1 citations1997: 3 citations1998: 31 citations1999: 24 citations2000: 40 citations2001: 47 citations2002: 77 citations2003: 47 citations2004: 71 citations2005: 93 citations2006: 103 citations2007: 139 citations2008: 122 citations2009: 133 citations2010: 147 citations2011: 212 citations2012: 222 citations2013: 222 citations2014: 272 citations2015: 325 citations2016: 427 citations2017: 583 citations2018: 954 citations2019: 1,451 citations2020: 1,807 citations2021: 2,074 citations2022: 1,765 citations2023: 1,756 citations2024: 2,001 citations2025: 1,893 citations2026: 638 citations2027: 3 citations1961: no citations, so this year is not shown1963–1964: no citations, so these years are not shown1966–1973: no citations, so these years are not shown1975–1980: no citations, so these years are not shown1982–1989: no citations, so these years are not shown1991–1994: no citations, so these years are not shown1996: no citations, so this year is not shown

Citation sources

Countries

World map of the countries and regions citing this authorUnited States: 4,005 citing papers, 21.8% of this breakdownChina: 3,124 citing papers, 17% of this breakdownUnited Kingdom: 1,345 citing papers, 7.3% of this breakdownCanada: 1,038 citing papers, 5.7% of this breakdownGermany: 924 citing papers, 5% of this breakdownIndia: 796 citing papers, 4.3% of this breakdownFrance: 601 citing papers, 3.3% of this breakdownAustralia: 441 citing papers, 2.4% of this breakdownSwitzerland: 369 citing papers, 2% of this breakdownSouth Korea: 367 citing papers, 2% of this breakdownItaly: 357 citing papers, 2% of this breakdownJapan: 338 citing papers, 1.9% of this breakdown
0%21.8%Other 25.3%

Institutions

Fields

  • Computer Science60.9%
  • Neuroscience12.5%
  • Engineering9.1%
  • Medicine8.2%
  • Decision Sciences2.6%
  • Biochemistry, Genetics and Molecular Biology1.1%
  • Other5.6%

Topics

  • Reinforcement Learning in Robotics10.1%
  • Brain Tumor Detection and Classification6.1%
  • Advanced Neural Network Applications6%
  • Medical Image Segmentation Techniques4.1%
  • Radiomics and Machine Learning in Medical Imaging2.4%
  • Domain Adaptation and Few-Shot Learning2.2%
  • Other69.1%

Coauthors

All papers

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  1. The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

    Authors: Bjoern H. Menze, András Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin S. Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, Levente Lanczi, Elizabeth R. Gerstner, Marc-André Weber, Tal Arbel, Brian B. Avants, Nicholas Ayache, Patricia Buendia, D. Louis Collins, Nicolas Cordier, Jason J. Corso, Antonio Criminisi, Tilak Das, Herve Delingette, Çagatay Demiralp, Christopher R. Durst, Michel Dojat, Senan Doyle, Joana Festa, Florence Forbes, Ezequiel Geremia, Ben Glocker, Polina Golland, Xiaotao Guo, Andac Hamamci, Khan M. Iftekharuddin, Raj Jena, Nigel M. John, Ender Konukoglu, Danial Lashkari, José Antonio Mariz, Raphael Meier, Sérgio Pereira, Doina Precup, Stephen J. Price, Tammy Riklin Raviv, Syed M. S. Reza, Michael T. Ryan, Duygu Sarikaya, Lawrence H. Schwartz, Hoo-Chang Shin, Jamie Shotton, Carlos A. Silva, Nuno J. Sousa, Nagesh K. Subbanna, Gábor Székely, Thomas J. Taylor, Owen M. Thomas, Nicholas J. Tustison, Gözde B. Ünal, Flor Vasseur, Max Wintermark, Dong Hye Ye, Liang Zhao, Binsheng Zhao, Darko Zikic, Marcel Prastawa, Mauricio Reyes, Koen Van Leemput - IEEE Transactions on Medical Imaging, IEEE Trans. Medical Imaging 2014 cited by 6,521

  2. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning

    Authors: Richard S. Sutton, Doina Precup, Satinder Singh - Artificial Intelligence, Artif. Intell. 1999 cited by 3,146

  3. 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

  4. Deep Reinforcement Learning That Matters

    Authors: Peter Henderson, Riashat Islam, Philip Bachman, Joelle Pineau, Doina Precup, David Meger - AAAI Conference on Artificial Intelligence 2018 cited by 1,567

  5. Deep learning, reinforcement learning, and world models

    Authors: Yutaka Matsuo, Yann LeCun, Maneesh Sahani, Doina Precup, David Silver, Masashi Sugiyama, Eiji Uchibe, Jun Morimoto - Neural Networks 2022 cited by 493

  6. Nash Learning from Human Feedback

    Authors: Rémi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Côme Fiegel, Andrea Michi, Marco Selvi, Sertan Girgin, Nikola Momchev, Olivier Bachem, Daniel J. Mankowitz, Doina Precup, Bilal Piot - ICML 2024 cited by 241

  7. Reward is enough

    Authors: David Silver, Satinder Singh, Doina Precup, Richard S. Sutton - Artificial Intelligence, Artif. Intell. 2021 cited by 385

  8. Towards Continual Reinforcement Learning: A Review and Perspectives

    Authors: Khimya Khetarpal, Matthew Riemer, Irina Rish, Doina Precup - Journal of Artificial Intelligence Research, J. Artif. Intell. Res. 2022 cited by 195

  9. Off-Policy Deep Reinforcement Learning without Exploration

    Authors: Scott Fujimoto, David Meger, Doina Precup - ICML 2019 cited by 2,095

  10. Conditional Computation in Neural Networks for faster models

    Authors: Emmanuel Bengio, Pierre-Luc Bacon, Joelle Pineau, Doina Precup - arXiv (Cornell University), CoRR 2015 cited by 230

  11. AndroidEnv: A Reinforcement Learning Platform for Android

    Authors: Daniel Toyama, Philippe Hamel, Anita Gergely, Gheorghe Comanici, Amelia Glaese, Zafarali Ahmed, Tyler Jackson, Shibl Mourad, Doina Precup - arXiv (Cornell University), CoRR 2021 cited by 78

  12. Algorithms for multi-armed bandit problems

    Authors: Volodymyr Kuleshov, Doina Precup - arXiv (Cornell University), CoRR 2014 cited by 239

  13. Is Heterophily A Real Nightmare For Graph Neural Networks To Do Node Classification?

    Authors: Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup - arXiv (Cornell University), CoRR 2021 cited by 96

  14. The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges

    Authors: Sitao Luan, Chenqing Hua, Qincheng Lu, Liheng Ma, Lirong Wu, Xinyu Wang, Minkai Xu, Xiao-Wen Chang, Doina Precup, Rex Ying, Stan Z. Li, Jian Tang, Guy Wolf, Stefanie Jegelka - arXiv (Cornell University), CoRR 2024 cited by 49

  15. Revisiting Heterophily For Graph Neural Networks

    Authors: Sitao Luan, Chenqing Hua, Qincheng Lu, Jiaqi Zhu, Mingde Zhao, Shuyuan Zhang, Xiao-Wen Chang, Doina Precup - Advances in Neural Information Processing Systems 35, NeurIPS 2022 cited by 325

  16. Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control

    Authors: Riashat Islam, Peter Henderson, Maziar Gomrokchi, Doina Precup - arXiv (Cornell University), CoRR 2017 cited by 198

  17. Learning with Pseudo-Ensembles

    Authors: Philip Bachman, Ouais Alsharif, Doina Precup - NIPS 2014 cited by 665

  18. A Survey of Exploration Methods in Reinforcement Learning

    Authors: Susan Amin, Maziar Gomrokchi, Harsh Satija, Herke van Hoof, Doina Precup - arXiv (Cornell University), CoRR 2021 cited by 67

  19. Fast gradient-descent methods for temporal-difference learning with linear function approximation

    Authors: Richard S. Sutton, Hamid Reza Maei, Doina Precup, Shalabh Bhatnagar, David Silver, Csaba Szepesvári, Eric Wiewiora - Conference on Machine Learning, ICML 2009 cited by 532

  20. Mixtures of Experts Unlock Parameter Scaling for Deep RL

    Authors: Johan S. Obando-Ceron, Ghada Sokar, Timon Willi, Clare Lyle, Jesse Farebrother, Jakob Nicolaus Foerster, Gintare Karolina Dziugaite, Doina Precup, Pablo Samuel Castro - ICML 2024 cited by 86

  21. COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation

    Authors: Jongmin Lee, Cosmin Paduraru, Daniel J. Mankowitz, Nicolas Heess, Doina Precup, Kee-Eung Kim, Arthur Guez - ICLR 2022 cited by 92

  22. Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation

    Authors: Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio - NeurIPS 2021 cited by 515

  23. Bisimulation Metrics for Continuous Markov Decision Processes

    Authors: Norm Ferns, Prakash Panangaden, Doina Precup - SIAM Journal on Computing, SIAM J. Comput. 2011 cited by 100

  24. Fast reinforcement learning with generalized policy updates

    Authors: André Barreto, Shaobo Hou, Diana Borsa, David Silver, Doina Precup - National Academy of Sciences, Proc. Natl. Acad. Sci. USA 2020 cited by 82