Calibrated Model-Based Deep Reinforcement Learning

19 June 2019

Papers citing "Calibrated Model-Based Deep Reinforcement Learning"

24 / 24 papers shown

Title
Zero-shot Model-based Reinforcement Learning using Large Language Models Khyati Khandelwal Youssef Attia El Hili Ambroise Odonnat Oussama Zekri Albert Thomas Giuseppe Paolo Maurizio Filippone I. Redko Jun Yao OffRL 198 3 0 17 Feb 2025
Calibrated Probabilistic Forecasts for Arbitrary Sequences Charles Marx Volodymyr Kuleshov Stefano Ermon AI4TS 127 1 0 27 Sep 2024
Modular Conformal Calibration Charles Marx Shengjia Zhao Willie Neiswanger Stefano Ermon 130 17 0 23 Jun 2022
A Verification Framework for Certifying Learning-Based Safety-Critical Aviation Systems Ali Baheri Hao Ren B. Johnson Pouria Razzaghi Peng Wei 95 7 0 09 May 2022
Approaching sales forecasting using recurrent neural networks and transformers Iván Vallés-Pérez E. Soria-Olivas M. Martínez-Sober Antonio J. Serrano J. Gómez-Sanchís Fernando Mateo AI4TS 91 42 0 16 Apr 2022
Towards PAC Multi-Object Detection and Tracking Shuo Li Sangdon Park Xiayan Ji Insup Lee Osbert Bastani 126 8 0 15 Apr 2022
Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation Volodymyr Kuleshov Shachi Deshpande UQCV BDL 557 34 0 14 Dec 2021
Uncertainty Toolbox: an Open-Source Library for Assessing, Visualizing, and Improving Uncertainty Quantification Youngseog Chung I. Char Han Guo J. Schneider Willie Neiswanger 131 76 0 21 Sep 2021
DROMO: Distributionally Robust Offline Model-based Policy Optimization Ruizhen Liu Dazhi Zhong Zhi-Cong Chen OffRL 107 3 0 15 Sep 2021
MBDP: A Model-based Approach to Achieve both Robustness and Sample Efficiency via Double Dropout Planning Wanpeng Zhang Xi Xiao Yaowen Yao Mingzhe Chen Dijun Luo OffRL 76 1 0 03 Aug 2021
PAC Prediction Sets Under Covariate Shift Sangdon Park Guang Cheng Insup Lee Osbert Bastani 154 47 0 17 Jun 2021
Offline Reinforcement Learning as One Big Sequence Modeling Problem Michael Janner Qiyang Li Sergey Levine OffRL 409 736 0 03 Jun 2021
Safety Enhancement for Deep Reinforcement Learning in Autonomous Separation Assurance Wei Guo Marc Brittain Peng Wei 157 19 0 05 May 2021
Combining Pessimism with Optimism for Robust and Efficient Model-Based Deep Reinforcement Learning Sebastian Curi Ilija Bogunovic Andreas Krause 113 18 0 18 Mar 2021
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNsInternational Conference on Learning Representations (ICLR), 2025 Cheng Wang Carolin (Haas) Lawrence Mathias Niepert UQCV 82 10 0 24 Nov 2020
Beyond Pinball Loss: Quantile Methods for Calibrated Uncertainty Quantification Youngseog Chung Willie Neiswanger I. Char J. Schneider UQCV 325 103 0 18 Nov 2020
Explaining Conditions for Reinforcement Learning Behaviors from Real and Imagined Data Aastha Acharya Rebecca L. Russell Nisar R. Ahmed OffRL 82 4 0 17 Nov 2020
Individual Calibration with Randomized ForecastingInternational Conference on Machine Learning (ICML), 2024 Shengjia Zhao Tengyu Ma Stefano Ermon 172 64 0 18 Jun 2020
Efficient Model-Based Reinforcement Learning through Optimistic Policy Search and PlanningNeural Information Processing Systems (NeurIPS), 2025 Sebastian Curi Felix Berkenkamp Andreas Krause 237 90 0 15 Jun 2020
Deep Reinforcement Learning with Weighted Q-Learning Andrea Cini Carlo DÉramo Jan Peters Cesare Alippi OffRL 91 9 0 20 Mar 2020
PAC Confidence Sets for Deep Neural Networks via Calibrated Prediction Sangdon Park Osbert Bastani Nikolai Matni Insup Lee UQCV 359 72 0 31 Dec 2019
Deep Dynamics Models for Learning Dexterous Manipulation Anusha Nagabandi K. Konolige Sergey Levine Vikash Kumar 336 437 0 25 Sep 2019
Verified Uncertainty Calibration Ananya Kumar Percy Liang Tengyu Ma 292 379 0 23 Sep 2019
Structured Variational Inference in Unstable Gaussian Process State Space Models Silvan Melchior Sebastian Curi Felix Berkenkamp Andreas Krause 151 4 0 16 Jul 2019