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1710.10044
Cited By
Distributional Reinforcement Learning with Quantile Regression
27 October 2017
Will Dabney
Mark Rowland
Marc G. Bellemare
Rémi Munos
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Papers citing
"Distributional Reinforcement Learning with Quantile Regression"
50 / 401 papers shown
Title
The Difficulty of Passive Learning in Deep Reinforcement Learning
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Automating Control of Overestimation Bias for Reinforcement Learning
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Dmitry Vetrov
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Offline Reinforcement Learning with Value-based Episodic Memory
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Yiqin Yang
Haotian Hu
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Bin Liang
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40
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Reinforcement Learning-Based Coverage Path Planning with Implicit Cellular Decomposition
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Olimpiya Saha
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18 Oct 2021
Value Penalized Q-Learning for Recommender Systems
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Lanqing Li
Xueqian Wang
Bo Yuan
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54
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15 Oct 2021
StARformer: Transformer with State-Action-Reward Representations for Visual Reinforcement Learning
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Kumara Kahatapitiya
Xiang Li
Michael S. Ryoo
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45
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0
12 Oct 2021
Offline Reinforcement Learning with Implicit Q-Learning
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Ashvin Nair
Sergey Levine
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214
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12 Oct 2021
Learning Pessimism for Robust and Efficient Off-Policy Reinforcement Learning
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Oya Celiktutan
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47
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07 Oct 2021
Offline RL With Resource Constrained Online Deployment
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A. Deshmukh
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Young Hun Jung
Abhishek Gupta
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13
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07 Oct 2021
The Benefits of Being Categorical Distributional: Uncertainty-aware Regularized Exploration in Reinforcement Learning
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Yingnan Zhao
Enze Shi
Yafei Wang
Xiaodong Yan
Bei Jiang
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07 Oct 2021
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Large Batch Experience Replay
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M. Geist
Emmanuel Rachelson
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56
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Simón Chamorro
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A Cramér Distance perspective on Quantile Regression based Distributional Reinforcement Learning
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Nicolas Bondoux
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The
f
f
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Qiang He
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Zhouyi Yang
Xiaoyu Chen
Xinwen Hou
Xianjie Zhang
Yu Liu
Guoliang Fan
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On Bonus-Based Exploration Methods in the Arcade Learning Environment
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Regularize! Don't Mix: Multi-Agent Reinforcement Learning without Explicit Centralized Structures
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Jason M. Traish
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Greedy UnMixing for Q-Learning in Multi-Agent Reinforcement Learning
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Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State Observations
Ke Sun
Yingnan Zhao
Shangling Jui
Linglong Kong
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Enabling risk-aware Reinforcement Learning for medical interventions through uncertainty decomposition
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Giulia Luise
Matthieu Komorowski
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16 Sep 2021
Exploration in Deep Reinforcement Learning: From Single-Agent to Multiagent Domain
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Tianpei Yang
Hongyao Tang
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Eden: A Unified Environment Framework for Booming Reinforcement Learning Algorithms
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Xiaoyu Wu
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...
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Deep Reinforcement Learning at the Edge of the Statistical Precipice
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Max Schwarzer
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High Performance Across Two Atari Paddle Games Using the Same Perceptual Control Architecture Without Training
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W. Mansell
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Learning Risk-aware Costmaps for Traversability in Challenging Environments
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Sharmita Dey
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41
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25 Jul 2021
Minimizing Safety Interference for Safe and Comfortable Automated Driving with Distributional Reinforcement Learning
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Tizian Engelgeh
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207
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Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning
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Harshita Diddee
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Conservative Offline Distributional Reinforcement Learning
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Osbert Bastani
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MMD-MIX: Value Function Factorisation with Maximum Mean Discrepancy for Cooperative Multi-Agent Reinforcement Learning
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Dapeng Li
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Automatic Risk Adaptation in Distributional Reinforcement Learning
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28
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Distributional Reinforcement Learning with Unconstrained Monotonic Neural Networks
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Antoine Wehenkel
Adrien Bolland
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06 Jun 2021
MICo: Improved representations via sampling-based state similarity for Markov decision processes
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Tyler Kastner
Prakash Panangaden
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48
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03 Jun 2021
Policies for the Dynamic Traveling Maintainer Problem with Alerts
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31 May 2021
GMAC: A Distributional Perspective on Actor-Critic Framework
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Ensemble Quantile Networks: Uncertainty-Aware Reinforcement Learning with Applications in Autonomous Driving
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Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
Yue Wu
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Non-decreasing Quantile Function Network with Efficient Exploration for Distributional Reinforcement Learning
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Interpretable performance analysis towards offline reinforcement learning: A dataset perspective
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Adapting to Reward Progressivity via Spectral Reinforcement Learning
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Universal Off-Policy Evaluation
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Off-Policy Risk Assessment in Contextual Bandits
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In Defense of the Paper
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Online and Offline Reinforcement Learning by Planning with a Learned Model
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Risk-Conditioned Distributional Soft Actor-Critic for Risk-Sensitive Navigation
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Bayesian Distributional Policy Gradients
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STEP: Stochastic Traversability Evaluation and Planning for Risk-Aware Off-road Navigation
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Flexible Model Aggregation for Quantile Regression
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SENTINEL: Taming Uncertainty with Ensemble-based Distributional Reinforcement Learning
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