Papers citing 'Statistics and Samples in Distributional Reinforcement Learning'

Title
Risk-Sensitive Q-Learning in Continuous Time with Application to Dynamic Portfolio Selection Chuhan Xie 172 0 0 02 Dec 2025
ES-C51: Expected Sarsa Based C51 Distributional Reinforcement Learning Algorithm Rijul Tandon Peter Vamplew Cameron Foale 72 0 0 16 Oct 2025
RM-RL: Role-Model Reinforcement Learning for Precise Robot Manipulation Xiangyu Chen Chuhao Zhou Yuxi Liu Jianfei Yang OffRL 132 0 0 16 Oct 2025
Phase Diagram of Dropout for Two-Layer Neural Networks in the Mean-Field Regime Lénaic Chizat Pierre Marion Yerkin Yesbay 94 0 0 08 Oct 2025
RAMAC: Multimodal Risk-Aware Offline Reinforcement Learning and the Role of Behavior Regularization Kai Fukazawa Kunal Mundada Iman Soltani OffRL 142 0 0 03 Oct 2025
Efficient Risk-sensitive Planning via Entropic Risk Measures Alexandre Marthe Samuel Bounan Aurélien Garivier Claire Vernade 326 2 0 27 Feb 2025
Tackling Uncertainties in Multi-Agent Reinforcement Learning through Integration of Agent Termination DynamicsAdaptive Agents and Multi-Agent Systems (AAMAS), 2025 S. Hazra P. Dasgupta Soumyajit Dey 278 0 0 21 Jan 2025
Bootstrapping Expectiles in Reinforcement Learning Pierre Clavier Emmanuel Rachelson E. L. Pennec Matthieu Geist OffRL 251 0 0 06 Jun 2024
Improving Actor-Critic Training with Steerable Action-Value Approximation Errors Bahareh Tasdighi Nicklas Werge Yi-Shan Wu M. Kandemir 152 0 0 06 Jun 2024
A Case for Validation Buffer in Pessimistic Actor-Critic Michal Nauman M. Ostaszewski Marek Cygan 218 0 0 01 Mar 2024
Distributional Bellman Operators over Mean EmbeddingsInternational Conference on Machine Learning (ICML), 2023 Wenliang Kevin Li Grégoire Delétang Matthew Aitchison Marcus Hutter Anian Ruoss Arthur Gretton Mark Rowland OffRL 205 4 0 09 Dec 2023
An introduction to reinforcement learning for neuroscienceNeurons, Behavior, Data analysis, and Theory (NBDT), 2023 Kristopher T. Jensen OOD OffRL AI4CE 103 8 0 13 Nov 2023
RiskQ: Risk-sensitive Multi-Agent Reinforcement Learning Value FactorizationNeural Information Processing Systems (NeurIPS), 2023 Siqi Shen Chennan Ma Chao Li Weiquan Liu Yongquan Fu Songzhu Mei Xinwang Liu Cheng-Yu Wang 180 19 0 03 Nov 2023
Beyond Average Return in Markov Decision ProcessesNeural Information Processing Systems (NeurIPS), 2023 Alexandre Marthe Aurélien Garivier Claire Vernade 210 10 0 31 Oct 2023
Distributional Soft Actor-Critic with Three RefinementsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023 Jingliang Duan Wenxuan Wang Liming Xiao Jiaxin Gao Shengbo Eben Li Chang Liu Ya-Qin Zhang Bo Cheng Keqiang Li OODD OffRL 237 4 0 09 Oct 2023
DRL-ORA: Distributional Reinforcement Learning with Online Risk Adaption Yupeng Wu Wenyun Li Wenjie Huang Chin Pang Ho OffRL 232 0 0 08 Oct 2023
Learning Risk-Aware Quadrupedal Locomotion using Distributional Reinforcement LearningIEEE International Conference on Robotics and Automation (ICRA), 2023 Lukas Schneider Jonas Frey Takahiro Miki Marco Hutter 256 16 0 25 Sep 2023
Value-Distributional Model-Based Reinforcement Learning Carlos E. Luis A. Bottero Julia Vinogradska Felix Berkenkamp Jan Peters OffRL 186 7 0 12 Aug 2023
Variance Control for Distributional Reinforcement LearningInternational Conference on Machine Learning (ICML), 2023 Qi Kuang Zhoufan Zhu Liwen Zhang Fan Zhou OffRL 283 4 0 30 Jul 2023
Cramer Type Distances for Learning Gaussian Mixture Models by Gradient Descent Ruichong Zhang 133 1 0 13 Jul 2023
Distributional Model Equivalence for Risk-Sensitive Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2023 Tyler Kastner Murat A. Erdogdu Amir-massoud Farahmand OffRL 244 7 0 04 Jul 2023
Is Risk-Sensitive Reinforcement Learning Properly Resolved? Ruiwen Zhou Minghuan Liu Kan Ren Xufang Luo Weinan Zhang Dongsheng Li 211 3 0 02 Jul 2023
Diverse Projection Ensembles for Distributional Reinforcement LearningInternational Conference on Learning Representations (ICLR), 2023 Moritz A. Zanger Wendelin Bohmer M. Spaan 207 7 0 12 Jun 2023
A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement LearningJournal of machine learning research (JMLR), 2023 Wei-Fang Sun Cheng-Kuang Lee Simon See Chun-Yi Lee OffRL 192 2 0 04 Jun 2023
The Statistical Benefits of Quantile Temporal-Difference Learning for Value EstimationInternational Conference on Machine Learning (ICML), 2023 Mark Rowland Yunhao Tang Clare Lyle Rémi Munos Marc G. Bellemare Will Dabney 179 13 0 28 May 2023
Distributional Reinforcement Learning with Dual Expectile-Quantile RegressionConference on Uncertainty in Artificial Intelligence (UAI), 2023 Sami Jullien Romain Deffayet J. Renders Paul T. Groth Maarten de Rijke OOD 297 1 0 26 May 2023
Learning Diverse Risk Preferences in Population-based Self-playAAAI Conference on Artificial Intelligence (AAAI), 2023 Y. Jiang Qihan Liu Xiaoteng Ma Chenghao Li Yiqin Yang Jun Yang Bin Liang Qianchuan Zhao 360 8 0 19 May 2023
Constrained Reinforcement Learning using Distributional Representation for Trustworthy Quadrotor UAV Tracking ControlIEEE Transactions on Automation Science and Engineering (IEEE TASE), 2023 Yanran Wang David E. Boyle 294 12 0 22 Feb 2023
Distributional GFlowNets with Quantile Flows Dinghuai Zhang L. Pan Ricky T. Q. Chen Aaron Courville Yoshua Bengio 253 31 0 11 Feb 2023
An Analysis of Quantile Temporal-Difference LearningJournal of machine learning research (JMLR), 2023 Mark Rowland Rémi Munos M. G. Azar Yunhao Tang Georg Ostrovski Anna Harutyunyan K. Tuyls Marc G. Bellemare Will Dabney 320 33 0 11 Jan 2023
Distributional Reward Estimation for Effective Multi-Agent Deep Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2022 Jifeng Hu Yanchao Sun Hechang Chen Sili Huang Haiyin Piao Yi-Ju Chang Lichao Sun 189 7 0 14 Oct 2022
Distributional Actor-Critic Ensemble for Uncertainty-Aware Continuous ControlIEEE International Joint Conference on Neural Network (IJCNN), 2022 T. Kanazawa Haiyan Wang Chetan Gupta UQCV 264 7 0 27 Jul 2022
The Nature of Temporal Difference Errors in Multi-step Distributional Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2022 Yunhao Tang Mark Rowland Rémi Munos Bernardo Avila-Pires Will Dabney Marc G. Bellemare OffRL 137 12 0 15 Jul 2022
A Simulation Environment and Reinforcement Learning Method for Waste Reduction Sami Jullien Mozhdeh Ariannezhad Paul T. Groth Maarten de Rijke OOD OffRL 194 4 0 30 May 2022
Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement LearningInternational Conference on Machine Learning (ICML), 2022 Harley Wiltzer David Meger Marc G. Bellemare 166 15 0 24 May 2022
Interpretable Stochastic Model Predictive Control using Distributional Reinforced Estimation for Quadrotor Tracking SystemsIEEE Conference on Decision and Control (CDC), 2022 Yanran Wang James O’Keeffe Qiuchen Qian David E. Boyle 103 4 0 14 May 2022
Distributional Reinforcement Learning by Sinkhorn DivergenceNeural Information Processing Systems (NeurIPS), 2022 Ke Sun Yingnan Zhao Wulong Liu Bei Jiang Linglong Kong 397 0 0 01 Feb 2022
Reinforcement Learning with Heterogeneous Data: Estimation and Inference Elynn Y. Chen Rui Song Michael I. Jordan OffRL 221 10 0 31 Jan 2022
Robustness and risk management via distributional dynamic programming Mastane Achab Gergely Neu 84 7 0 28 Dec 2021
Deep Reinforcement Learning Policies Learn Shared Adversarial Features Across MDPs Ezgi Korkmaz 88 27 0 16 Dec 2021
Offline Reinforcement Learning with Value-based Episodic Memory Xiaoteng Ma Yiqin Yang Haotian Hu Qihan Liu Jun Yang Chongjie Zhang Qianchuan Zhao Bin Liang OffRL 198 46 0 19 Oct 2021
The Benefits of Being Categorical Distributional: Uncertainty-aware Regularized Exploration in Reinforcement Learning Ke Sun Yingnan Zhao Enze Shi Yafei Wang Xiaodong Yan Bei Jiang Linglong Kong OOD OffRL UQCV 227 2 0 07 Oct 2021
Conservative Offline Distributional Reinforcement Learning Yecheng Jason Ma Dinesh Jayaraman Osbert Bastani OffRL 200 95 0 12 Jul 2021
Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks Thibaut Théate Antoine Wehenkel Adrien Bolland Gilles Louppe D. Ernst 153 8 0 06 Jun 2021
GMAC: A Distributional Perspective on Actor-Critic FrameworkInternational Conference on Machine Learning (ICML), 2021 D. W. Nam Younghoon Kim Chan Y. Park 185 21 0 24 May 2021
Universal Off-Policy EvaluationNeural Information Processing Systems (NeurIPS), 2021 Yash Chandak S. Niekum Bruno C. da Silva Erik Learned-Miller Emma Brunskill Philip S. Thomas OffRL ELM 244 57 0 26 Apr 2021
Bayesian Distributional Policy GradientsAAAI Conference on Artificial Intelligence (AAAI), 2021 Luchen Li A. Faisal BDL OffRL 166 11 0 20 Mar 2021
SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement LearningConference on Uncertainty in Artificial Intelligence (UAI), 2021 Hannes Eriksson D. Basu Mina Alibeigi Christos Dimitrakakis OffRL 147 19 0 22 Feb 2021
DFAC Framework: Factorizing the Value Function via Quantile Mixture for Multi-Agent Distributional Q-LearningInternational Conference on Machine Learning (ICML), 2021 Wei-Fang Sun Cheng-Kuang Lee Chun-Yi Lee OffRL 170 52 0 16 Feb 2021
Tactical Optimism and Pessimism for Deep Reinforcement LearningNeural Information Processing Systems (NeurIPS), 2021 Theodore H. Moskovitz Jack Parker-Holder Aldo Pacchiano Michael Arbel Sai Li 291 68 0 07 Feb 2021