More from the Same Authors

• 2021 : Data Sharing without Rewards in Multi-Task Offline Reinforcement Learning »
  Tianhe Yu · Aviral Kumar · Yevgen Chebotar · Chelsea Finn · Sergey Levine · Karol Hausman
• 2021 : Should I Run Offline Reinforcement Learning or Behavioral Cloning? »
  Aviral Kumar · Joey Hong · Anikait Singh · Sergey Levine
• 2021 : DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization »
  Aviral Kumar · Rishabh Agarwal · Tengyu Ma · Aaron Courville · George Tucker · Sergey Levine
• 2021 : Offline Policy Selection under Uncertainty »
  Mengjiao (Sherry) Yang · Bo Dai · Ofir Nachum · George Tucker · Dale Schuurmans
• 2022 : Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes »
  Aviral Kumar · Rishabh Agarwal · XINYANG GENG · George Tucker · Sergey Levine
• 2022 : Imitation Is Not Enough: Robustifying Imitation with Reinforcement Learning for Challenging Driving Scenarios »
  Yiren Lu · Yiren Lu · Yiren Lu · Justin Fu · George Tucker · Xinlei Pan · Eli Bronstein · Rebecca Roelofs · Benjamin Sapp · Brandyn White · Aleksandra Faust · Shimon Whiteson · Dragomir Anguelov · Sergey Levine
• 2022 : Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes »
  Aviral Kumar · Rishabh Agarwal · XINYANG GENG · George Tucker · Sergey Levine
• 2022 Workshop: 3rd Offline Reinforcement Learning Workshop: Offline RL as a "Launchpad" »
  Aviral Kumar · Rishabh Agarwal · Aravind Rajeswaran · Wenxuan Zhou · George Tucker · Doina Precup · Aviral Kumar
• 2022 Poster: Oracle Inequalities for Model Selection in Offline Reinforcement Learning »
  Jonathan N Lee · George Tucker · Ofir Nachum · Bo Dai · Emma Brunskill
• 2021 : Speaker Intro »
  Aviral Kumar · George Tucker
• 2021 : Invited Speaker Panel »
  Sham Kakade · Minmin Chen · Philip Thomas · Angela Schoellig · Barbara Engelhardt · Doina Precup · George Tucker
• 2021 : Speaker Intro »
  Rishabh Agarwal · Aviral Kumar
• 2021 : Speaker Intro »
  Rishabh Agarwal · Aviral Kumar
• 2021 Workshop: Offline Reinforcement Learning »
  Rishabh Agarwal · Aviral Kumar · George Tucker · Justin Fu · Nan Jiang · Doina Precup · Aviral Kumar
• 2021 : Opening Remarks »
  Rishabh Agarwal · Aviral Kumar
• 2021 : DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization Q&A »
  Aviral Kumar · Rishabh Agarwal · Tengyu Ma · Aaron Courville · George Tucker · Sergey Levine
• 2021 : DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization »
  Aviral Kumar · Rishabh Agarwal · Tengyu Ma · Aaron Courville · George Tucker · Sergey Levine
• 2021 Poster: COMBO: Conservative Offline Model-Based Policy Optimization »
  Tianhe Yu · Aviral Kumar · Rafael Rafailov · Aravind Rajeswaran · Sergey Levine · Chelsea Finn
• 2021 Poster: Coupled Gradient Estimators for Discrete Latent Variables »
  Zhe Dong · Andriy Mnih · George Tucker
• 2021 Poster: Conservative Data Sharing for Multi-Task Offline Reinforcement Learning »
  Tianhe Yu · Aviral Kumar · Yevgen Chebotar · Karol Hausman · Sergey Levine · Chelsea Finn
• 2021 Poster: Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability »
  Dibya Ghosh · Jad Rahme · Aviral Kumar · Amy Zhang · Ryan Adams · Sergey Levine
• 2020 : Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization »
  Brandon Trabucco · Aviral Kumar · XINYANG GENG · Sergey Levine
• 2020 : Conservative Objective Models: A Simple Approach to Effective Model-Based Optimization »
  Brandon Trabucco · Aviral Kumar · XINYANG GENG · Sergey Levine
• 2020 : Panel »
  Emma Brunskill · Nan Jiang · Nando de Freitas · Finale Doshi-Velez · Sergey Levine · John Langford · Lihong Li · George Tucker · Rishabh Agarwal · Aviral Kumar
• 2020 Workshop: Offline Reinforcement Learning »
  Aviral Kumar · Rishabh Agarwal · George Tucker · Lihong Li · Doina Precup · Aviral Kumar
• 2020 : Introduction »
  Aviral Kumar · George Tucker · Rishabh Agarwal
• 2020 Poster: DisARM: An Antithetic Gradient Estimator for Binary Latent Variables »
  Zhe Dong · Andriy Mnih · George Tucker
• 2020 Spotlight: DisARM: An Antithetic Gradient Estimator for Binary Latent Variables »
  Zhe Dong · Andriy Mnih · George Tucker
• 2020 Poster: Conservative Q-Learning for Offline Reinforcement Learning »
  Aviral Kumar · Aurick Zhou · George Tucker · Sergey Levine
• 2020 Poster: One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL »
  Saurabh Kumar · Aviral Kumar · Sergey Levine · Chelsea Finn
• 2020 Tutorial: (Track3) Offline Reinforcement Learning: From Algorithm Design to Practical Applications »
  Sergey Levine · Aviral Kumar
• 2019 Poster: Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction »
  Aviral Kumar · Justin Fu · George Tucker · Sergey Levine
• 2019 Poster: Graph Normalizing Flows »
  Jenny Liu · Aviral Kumar · Jimmy Ba · Jamie Kiros · Kevin Swersky
• 2019 Poster: Energy-Inspired Models: Learning with Sampler-Induced Distributions »
  Dieterich Lawson · George Tucker · Bo Dai · Rajesh Ranganath
• 2019 Poster: Don't Blame the ELBO! A Linear VAE Perspective on Posterior Collapse »
  James Lucas · George Tucker · Roger Grosse · Mohammad Norouzi
• 2018 : Spotlights »
  Guangneng Hu · Ke Li · Aviral Kumar · Phi Vu Tran · Samuel G. Fadel · Rita Kuznetsova · Bong-Nam Kang · Behrouz Haji Soleimani · Jinwon An · Nathan de Lara · Anjishnu Kumar · Tillman Weyde · Melanie Weber · Kristen Altenburger · Saeed Amizadeh · Xiaoran Xu · Yatin Nandwani · Yang Guo · Maria Pacheco · William Fedus · Guillaume Jaume · Yuka Yoneda · Yunpu Ma · Yunsheng Bai · Berk Kapicioglu · Maximilian Nickel · Fragkiskos Malliaros · Beier Zhu · Aleksandar Bojchevski · Joshua Joseph · Gemma Roig · Esma Balkir · Xander Steenbrugge
• 2018 Poster: Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion »
  Jacob Buckman · Danijar Hafner · George Tucker · Eugene Brevdo · Honglak Lee
• 2018 Oral: Sample-Efficient Reinforcement Learning with Stochastic Ensemble Value Expansion »
  Jacob Buckman · Danijar Hafner · George Tucker · Eugene Brevdo · Honglak Lee
• 2017 Poster: REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models »
  George Tucker · Andriy Mnih · Chris J Maddison · John Lawson · Jascha Sohl-Dickstein
• 2017 Oral: REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models »
  George Tucker · Andriy Mnih · Chris J Maddison · John Lawson · Jascha Sohl-Dickstein
• 2017 Poster: Filtering Variational Objectives »
  Chris Maddison · John Lawson · George Tucker · Nicolas Heess · Mohammad Norouzi · Andriy Mnih · Arnaud Doucet · Yee Teh