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Offline reinforcement learning (RL) refers to the problem of learning policies entirely from a batch of previously collected data. This problem setting is compelling, because it offers the promise of utilizing large, diverse, previously collected datasets to acquire policies without any costly or dangerous active exploration, but it is also exceptionally difficult, due to the distributional shift between the offline training data and the learned policy. While there has been significant progress in model-free offline RL, the most successful prior methods constrain the policy to the support of the data, precluding generalization to new states. In this paper, we observe that an existing model-based RL algorithm on its own already produces significant gains in the offline setting, as compared to model-free approaches, despite not being designed for this setting. However, although many standard model-based RL methods already estimate the uncertainty of their model, they do not by themselves provide a mechanism to avoid the issues associated with distributional shift in the offline setting. We therefore propose to modify existing model-based RL methods to address these issues by casting offline model-based RL into a penalized MDP framework. We theoretically show that, by using this penalized MDP, we are maximizing a lower bound of the return in the true MDP. Based on our theoretical results, we propose a new model-based offline RL algorithm that applies the variance of a Lipschitz-regularized model as a penalty to the reward function. We find that this algorithm outperforms both standard model-based RL methods and existing state-of-the-art model-free offline RL approaches on existing offline RL benchmarks, as well as two challenging continuous control tasks that require generalizing from data collected for a different task.
Author Information
Tianhe Yu (Stanford University)
Garrett Thomas (Stanford University)
Lantao Yu (Stanford University)
Stefano Ermon (Stanford)
James Zou (Stanford University)
Sergey Levine (UC Berkeley)
Chelsea Finn (Stanford)
Tengyu Ma (Stanford University)
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2021 Poster: HyperSPNs: Compact and Expressive Probabilistic Circuits »
Andy Shih · Dorsa Sadigh · Stefano Ermon -
2021 Poster: Which Mutual-Information Representation Learning Objectives are Sufficient for Control? »
Kate Rakelly · Abhishek Gupta · Carlos Florensa · Sergey Levine -
2021 Poster: Imitation with Neural Density Models »
Kuno Kim · Akshat Jindal · Yang Song · Jiaming Song · Yanan Sui · Stefano Ermon -
2021 Poster: COMBO: Conservative Offline Model-Based Policy Optimization »
Tianhe Yu · Aviral Kumar · Rafael Rafailov · Aravind Rajeswaran · Sergey Levine · Chelsea Finn -
2021 Poster: Reliable Decisions with Threshold Calibration »
Roshni Sahoo · Shengjia Zhao · Alyssa Chen · Stefano Ermon -
2021 Poster: Outcome-Driven Reinforcement Learning via Variational Inference »
Tim G. J. Rudner · Vitchyr Pong · Rowan McAllister · Yarin Gal · Sergey Levine -
2021 Poster: D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation »
Abhishek Sinha · Jiaming Song · Chenlin Meng · Stefano Ermon -
2021 Poster: Improving Compositionality of Neural Networks by Decoding Representations to Inputs »
Mike Wu · Noah Goodman · Stefano Ermon -
2021 Poster: Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis »
Yutong He · Dingjie Wang · Nicholas Lai · William Zhang · Chenlin Meng · Marshall Burke · David Lobell · Stefano Ermon -
2021 Poster: Bayesian Adaptation for Covariate Shift »
Aurick Zhou · Sergey Levine -
2021 Poster: Calibrating Predictions to Decisions: A Novel Approach to Multi-Class Calibration »
Shengjia Zhao · Michael Kim · Roshni Sahoo · Tengyu Ma · Stefano Ermon -
2021 Poster: Estimating High Order Gradients of the Data Distribution by Denoising »
Chenlin Meng · Yang Song · Wenzhe Li · Stefano Ermon -
2021 Poster: Offline Reinforcement Learning as One Big Sequence Modeling Problem »
Michael Janner · Qiyang Li · Sergey Levine -
2021 Poster: Maximum Likelihood Training of Score-Based Diffusion Models »
Yang Song · Conor Durkan · Iain Murray · Stefano Ermon -
2021 Poster: Pragmatic Image Compression for Human-in-the-Loop Decision-Making »
Sid Reddy · Anca Dragan · Sergey Levine -
2021 Poster: Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification »
Ben Eysenbach · Sergey Levine · Russ Salakhutdinov -
2021 Poster: Pseudo-Spherical Contrastive Divergence »
Lantao Yu · Jiaming Song · Yang Song · Stefano Ermon -
2021 Poster: IQ-Learn: Inverse soft-Q Learning for Imitation »
Divyansh Garg · Shuvam Chakraborty · Chris Cundy · Jiaming Song · Stefano Ermon -
2021 Poster: Safe Reinforcement Learning by Imagining the Near Future »
Garrett Thomas · Yuping Luo · Tengyu Ma -
2021 Poster: Information is Power: Intrinsic Control via Information Capture »
Nicholas Rhinehart · Jenny Wang · Glen Berseth · John Co-Reyes · Danijar Hafner · Chelsea Finn · Sergey Levine -
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: Meta-learning with an Adaptive Task Scheduler »
Huaxiu Yao · Yu Wang · Ying Wei · Peilin Zhao · Mehrdad Mahdavi · Defu Lian · Chelsea Finn -
2021 Poster: CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation »
Yusuke Tashiro · Jiaming Song · Yang Song · Stefano Ermon -
2021 Poster: PiRank: Scalable Learning To Rank via Differentiable Sorting »
Robin Swezey · Aditya Grover · Bruno Charron · Stefano Ermon -
2021 Poster: Noether Networks: meta-learning useful conserved quantities »
Ferran Alet · Dylan Doblar · Allan Zhou · Josh Tenenbaum · Kenji Kawaguchi · 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 -
2021 Poster: Differentiable Annealed Importance Sampling and the Perils of Gradient Noise »
Guodong Zhang · Kyle Hsu · Jianing Li · Chelsea Finn · Roger Grosse -
2021 Poster: BCD Nets: Scalable Variational Approaches for Bayesian Causal Discovery »
Chris Cundy · Aditya Grover · Stefano Ermon -
2021 Poster: Autonomous Reinforcement Learning via Subgoal Curricula »
Archit Sharma · Abhishek Gupta · Sergey Levine · Karol Hausman · Chelsea Finn -
2021 Poster: Adaptive Risk Minimization: Learning to Adapt to Domain Shift »
Marvin Zhang · Henrik Marklund · Nikita Dhawan · Abhishek Gupta · Sergey Levine · Chelsea Finn -
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 Discussion & Closing »
Yejin Choi · Alexei Efros · Chelsea Finn · Kristen Grauman · Quoc V Le · Yann LeCun · Ruslan Salakhutdinov · Eric Xing -
2020 : QA: Chelsea Finn »
Chelsea Finn -
2020 : Mini-panel discussion 3 - Prioritizing Real World RL Challenges »
Chelsea Finn · Thomas Dietterich · Angela Schoellig · Anca Dragan · Anusha Nagabandi · Doina Precup -
2020 : Invited Talk: Chelsea Finn »
Chelsea Finn -
2020 : Keynote: Chelsea Finn »
Chelsea Finn -
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 : Contributed Talk: MaxEnt RL and Robust Control »
Benjamin Eysenbach · Sergey Levine -
2020 : Invited talk - Underfitting and Uncertainty in Self-Supervised Predictive Models »
Chelsea Finn -
2020 : Stefano Emron - Generative Modeling via Denoising »
Stefano Ermon -
2020 Workshop: Deep Reinforcement Learning »
Pieter Abbeel · Chelsea Finn · Joelle Pineau · David Silver · Satinder Singh · Coline Devin · Misha Laskin · Kimin Lee · Janarthanan Rajendran · Vivek Veeriah -
2020 Poster: Weakly-Supervised Reinforcement Learning for Controllable Behavior »
Lisa Lee · Benjamin Eysenbach · Russ Salakhutdinov · Shixiang (Shane) Gu · Chelsea Finn -
2020 Poster: Model Inversion Networks for Model-Based Optimization »
Aviral Kumar · Sergey Levine -
2020 Poster: Improved Techniques for Training Score-Based Generative Models »
Yang Song · Stefano Ermon -
2020 Poster: Federated Accelerated Stochastic Gradient Descent »
Honglin Yuan · Tengyu Ma -
2020 Poster: Neuron Shapley: Discovering the Responsible Neurons »
Amirata Ghorbani · James Zou -
2020 Poster: Probabilistic Circuits for Variational Inference in Discrete Graphical Models »
Andy Shih · Stefano Ermon -
2020 Poster: Efficient Learning of Generative Models via Finite-Difference Score Matching »
Tianyu Pang · Kun Xu · Chongxuan LI · Yang Song · Stefano Ermon · Jun Zhu -
2020 Poster: Continual Learning of Control Primitives : Skill Discovery via Reset-Games »
Kelvin Xu · Siddharth Verma · Chelsea Finn · Sergey Levine -
2020 Poster: Belief Propagation Neural Networks »
Jonathan Kuck · Shuvam Chakraborty · Hao Tang · Rachel Luo · Jiaming Song · Ashish Sabharwal · Stefano Ermon -
2020 Poster: Gradient Surgery for Multi-Task Learning »
Tianhe Yu · Saurabh Kumar · Abhishek Gupta · Sergey Levine · Karol Hausman · Chelsea Finn -
2020 Poster: Self-training Avoids Using Spurious Features Under Domain Shift »
Yining Chen · Colin Wei · Ananya Kumar · Tengyu Ma -
2020 Poster: FrugalML: How to use ML Prediction APIs more accurately and cheaply »
Lingjiao Chen · Matei Zaharia · James Zou -
2020 Poster: Beyond Lazy Training for Over-parameterized Tensor Decomposition »
Xiang Wang · Chenwei Wu · Jason Lee · Tengyu Ma · Rong Ge -
2020 Oral: FrugalML: How to use ML Prediction APIs more accurately and cheaply »
Lingjiao Chen · Matei Zaharia · James Zou -
2020 Poster: HiPPO: Recurrent Memory with Optimal Polynomial Projections »
Albert Gu · Tri Dao · Stefano Ermon · Atri Rudra · Christopher Ré -
2020 Poster: Continuous Meta-Learning without Tasks »
James Harrison · Apoorva Sharma · Chelsea Finn · Marco Pavone -
2020 Spotlight: HiPPO: Recurrent Memory with Optimal Polynomial Projections »
Albert Gu · Tri Dao · Stefano Ermon · Atri Rudra · Christopher Ré -
2020 Poster: Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement »
Benjamin Eysenbach · XINYANG GENG · Sergey Levine · Russ Salakhutdinov -
2020 Poster: Model-based Adversarial Meta-Reinforcement Learning »
Zichuan Lin · Garrett Thomas · Guangwen Yang · Tengyu Ma -
2020 Poster: Conservative Q-Learning for Offline Reinforcement Learning »
Aviral Kumar · Aurick Zhou · George Tucker · Sergey Levine -
2020 Poster: Autoregressive Score Matching »
Chenlin Meng · Lantao Yu · Yang Song · Jiaming Song · Stefano Ermon -
2020 Oral: Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement »
Benjamin Eysenbach · XINYANG GENG · Sergey Levine · Russ Salakhutdinov -
2020 Tutorial: (Track3) Offline Reinforcement Learning: From Algorithm Design to Practical Applications Q&A »
Sergey Levine · Aviral Kumar -
2020 Poster: Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction »
Michael Janner · Igor Mordatch · 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 Poster: Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors »
Karl Pertsch · Oleh Rybkin · Frederik Ebert · Shenghao Zhou · Dinesh Jayaraman · Chelsea Finn · Sergey Levine -
2020 Poster: Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model »
Alex X. Lee · Anusha Nagabandi · Pieter Abbeel · Sergey Levine -
2020 Poster: Diversity can be Transferred: Output Diversification for White- and Black-box Attacks »
Yusuke Tashiro · Yang Song · Stefano Ermon -
2020 Poster: Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design »
Michael Dennis · Natasha Jaques · Eugene Vinitsky · Alexandre Bayen · Stuart Russell · Andrew Critch · Sergey Levine -
2020 Poster: DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction »
Aviral Kumar · Abhishek Gupta · Sergey Levine -
2020 Poster: Multi-label Contrastive Predictive Coding »
Jiaming Song · Stefano Ermon -
2020 Spotlight: DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction »
Aviral Kumar · Abhishek Gupta · Sergey Levine -
2020 Oral: Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design »
Michael Dennis · Natasha Jaques · Eugene Vinitsky · Alexandre Bayen · Stuart Russell · Andrew Critch · Sergey Levine -
2020 Oral: Multi-label Contrastive Predictive Coding »
Jiaming Song · Stefano Ermon -
2020 Tutorial: (Track3) Offline Reinforcement Learning: From Algorithm Design to Practical Applications »
Sergey Levine · Aviral Kumar -
2019 : Poster and Coffee Break 2 »
Karol Hausman · Kefan Dong · Ken Goldberg · Lihong Li · Lin Yang · Lingxiao Wang · Lior Shani · Liwei Wang · Loren Amdahl-Culleton · Lucas Cassano · Marc Dymetman · Marc Bellemare · Marcin Tomczak · Margarita Castro · Marius Kloft · Marius-Constantin Dinu · Markus Holzleitner · Martha White · Mengdi Wang · Michael Jordan · Mihailo Jovanovic · Ming Yu · Minshuo Chen · Moonkyung Ryu · Muhammad Zaheer · Naman Agarwal · Nan Jiang · Niao He · Nikolaus Yasui · Nikos Karampatziakis · Nino Vieillard · Ofir Nachum · Olivier Pietquin · Ozan Sener · Pan Xu · Parameswaran Kamalaruban · Paul Mineiro · Paul Rolland · Philip Amortila · Pierre-Luc Bacon · Prakash Panangaden · Qi Cai · Qiang Liu · Quanquan Gu · Raihan Seraj · Richard Sutton · Rick Valenzano · Robert Dadashi · Rodrigo Toro Icarte · Roshan Shariff · Roy Fox · Ruosong Wang · Saeed Ghadimi · Samuel Sokota · Sean Sinclair · Sepp Hochreiter · Sergey Levine · Sergio Valcarcel Macua · Sham Kakade · Shangtong Zhang · Sheila McIlraith · Shie Mannor · Shimon Whiteson · Shuai Li · Shuang Qiu · Wai Lok Li · Siddhartha Banerjee · Sitao Luan · Tamer Basar · Thinh Doan · Tianhe Yu · Tianyi Liu · Tom Zahavy · Toryn Klassen · Tuo Zhao · Vicenç Gómez · Vincent Liu · Volkan Cevher · Wesley Suttle · Xiao-Wen Chang · Xiaohan Wei · Xiaotong Liu · Xingguo Li · Xinyi Chen · Xingyou Song · Yao Liu · YiDing Jiang · Yihao Feng · Yilun Du · Yinlam Chow · Yinyu Ye · Yishay Mansour · · Yonathan Efroni · Yongxin Chen · Yuanhao Wang · Bo Dai · Chen-Yu Wei · Harsh Shrivastava · Hongyang Zhang · Qinqing Zheng · SIDDHARTHA SATPATHI · Xueqing Liu · Andreu Vall -
2019 : Poster Presentations »
Rahul Mehta · Andrew Lampinen · Binghong Chen · Sergio Pascual-Diaz · Jordi Grau-Moya · Aldo Faisal · Jonathan Tompson · Yiren Lu · Khimya Khetarpal · Martin Klissarov · Pierre-Luc Bacon · Doina Precup · Thanard Kurutach · Aviv Tamar · Pieter Abbeel · Jinke He · Maximilian Igl · Shimon Whiteson · Wendelin Boehmer · Raphaël Marinier · Olivier Pietquin · Karol Hausman · Sergey Levine · Chelsea Finn · Tianhe Yu · Lisa Lee · Benjamin Eysenbach · Emilio Parisotto · Eric Xing · Ruslan Salakhutdinov · Hongyu Ren · Anima Anandkumar · Deepak Pathak · Christopher Lu · Trevor Darrell · Alexei Efros · Phillip Isola · Feng Liu · Bo Han · Gang Niu · Masashi Sugiyama · Saurabh Kumar · Janith Petangoda · Johan Ferret · James McClelland · Kara Liu · Animesh Garg · Robert Lange -
2019 : Poster Session »
Matthia Sabatelli · Adam Stooke · Amir Abdi · Paulo Rauber · Leonard Adolphs · Ian Osband · Hardik Meisheri · Karol Kurach · Johannes Ackermann · Matt Benatan · GUO ZHANG · Chen Tessler · Dinghan Shen · Mikayel Samvelyan · Riashat Islam · Murtaza Dalal · Luke Harries · Andrey Kurenkov · Konrad Żołna · Sudeep Dasari · Kristian Hartikainen · Ofir Nachum · Kimin Lee · Markus Holzleitner · Vu Nguyen · Francis Song · Christopher Grimm · Felipe Leno da Silva · Yuping Luo · Yifan Wu · Alex Lee · Thomas Paine · Wei-Yang Qu · Daniel Graves · Yannis Flet-Berliac · Yunhao Tang · Suraj Nair · Matthew Hausknecht · Akhil Bagaria · Simon Schmitt · Bowen Baker · Paavo Parmas · Benjamin Eysenbach · Lisa Lee · Siyu Lin · Daniel Seita · Abhishek Gupta · Riley Simmons-Edler · Yijie Guo · Kevin Corder · Vikash Kumar · Scott Fujimoto · Adam Lerer · Ignasi Clavera Gilaberte · Nicholas Rhinehart · Ashvin Nair · Ge Yang · Lingxiao Wang · Sungryull Sohn · J. Fernando Hernandez-Garcia · Xian Yeow Lee · Rupesh Srivastava · Khimya Khetarpal · Chenjun Xiao · Luckeciano Carvalho Melo · Rishabh Agarwal · Tianhe Yu · Glen Berseth · Devendra Singh Chaplot · Jie Tang · Anirudh Srinivasan · Tharun Kumar Reddy Medini · Aaron Havens · Misha Laskin · Asier Mujika · Rohan Saphal · Joseph Marino · Alex Ray · Joshua Achiam · Ajay Mandlekar · Zhuang Liu · Danijar Hafner · Zhiwen Tang · Ted Xiao · Michael Walton · Jeff Druce · Ferran Alet · Zhang-Wei Hong · Stephanie Chan · Anusha Nagabandi · Hao Liu · Hao Sun · Ge Liu · Dinesh Jayaraman · John Co-Reyes · Sophia Sanborn -
2019 : Poster Session »
Ethan Harris · Tom White · Oh Hyeon Choung · Takashi Shinozaki · Dipan Pal · Katherine L. Hermann · Judy Borowski · Camilo Fosco · Chaz Firestone · Vijay Veerabadran · Benjamin Lahner · Chaitanya Ryali · Fenil Doshi · Pulkit Singh · Sharon Zhou · Michel Besserve · Michael Chang · Anelise Newman · Mahesan Niranjan · Jonathon Hare · Daniela Mihai · Marios Savvides · Simon Kornblith · Christina M Funke · Aude Oliva · Virginia de Sa · Dmitry Krotov · Colin Conwell · George Alvarez · Alex Kolchinski · Shengjia Zhao · Mitchell Gordon · Michael Bernstein · Stefano Ermon · Arash Mehrjou · Bernhard Schölkopf · John Co-Reyes · Michael Janner · Jiajun Wu · Josh Tenenbaum · Sergey Levine · Yalda Mohsenzadeh · Zhenglong Zhou -
2019 : Phenotype »
Nir HaCohen · David Reshef · Matthew Johnson · Sam Morris · Aurel Nagy · Gokcen Eraslan · Meromit Singer · Eliezer Van Allen · Smita Krishnaswamy · Casey Greene · Scott Linderman · Alexander Wiltschko · Dylan Kotliar · James Zou · Brendan Bulik-Sullivan -
2019 : Coffee/Poster session 1 »
Shiro Takagi · Khurram Javed · Johanna Sommer · Amr Sharaf · Pierluca D'Oro · Ying Wei · Sivan Doveh · Colin White · Santiago Gonzalez · Cuong Nguyen · Mao Li · Tianhe Yu · Tiago Ramalho · Masahiro Nomura · Ahsan Alvi · Jean-Francois Ton · W. Ronny Huang · Jessica Lee · Sebastian Flennerhag · Michael Zhang · Abram Friesen · Paul Blomstedt · Alina Dubatovka · Sergey Bartunov · Subin Yi · Iaroslav Shcherbatyi · Christian Simon · Zeyuan Shang · David MacLeod · Lu Liu · Liam Fowl · Diego Mesquita · Deirdre Quillen -
2019 Workshop: Learning with Rich Experience: Integration of Learning Paradigms »
Zhiting Hu · Andrew Wilson · Chelsea Finn · Lisa Lee · Taylor Berg-Kirkpatrick · Ruslan Salakhutdinov · Eric Xing -
2019 Workshop: Information Theory and Machine Learning »
Shengjia Zhao · Jiaming Song · Yanjun Han · Kristy Choi · Pratyusha Kalluri · Ben Poole · Alex Dimakis · Jiantao Jiao · Tsachy Weissman · Stefano Ermon -
2019 Poster: Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss »
Kaidi Cao · Colin Wei · Adrien Gaidon · Nikos Arechiga · Tengyu Ma -
2019 Poster: Wasserstein Dependency Measure for Representation Learning »
Sherjil Ozair · Corey Lynch · Yoshua Bengio · Aaron van den Oord · Sergey Levine · Pierre Sermanet -
2019 Poster: Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel »
Colin Wei · Jason Lee · Qiang Liu · Tengyu Ma -
2019 Spotlight: Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel »
Colin Wei · Jason Lee · Qiang Liu · Tengyu Ma -
2019 Poster: Towards Automatic Concept-based Explanations »
Amirata Ghorbani · James Wexler · James Zou · Been Kim -
2019 Poster: Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations. »
Sawyer Birnbaum · Volodymyr Kuleshov · Zayd Enam · Pang Wei Koh · Stefano Ermon -
2019 Poster: Planning with Goal-Conditioned Policies »
Soroush Nasiriany · Vitchyr Pong · Steven Lin · Sergey Levine -
2019 Poster: Search on the Replay Buffer: Bridging Planning and Reinforcement Learning »
Benjamin Eysenbach · Russ Salakhutdinov · Sergey Levine -
2019 Poster: MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies »
Xue Bin Peng · Michael Chang · Grace Zhang · Pieter Abbeel · Sergey Levine -
2019 Poster: MintNet: Building Invertible Neural Networks with Masked Convolutions »
Yang Song · Chenlin Meng · Stefano Ermon -
2019 Poster: Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting »
Aditya Grover · Jiaming Song · Ashish Kapoor · Kenneth Tran · Alekh Agarwal · Eric Horvitz · Stefano Ermon -
2019 Poster: Meta-Inverse Reinforcement Learning with Probabilistic Context Variables »
Lantao Yu · Tianhe Yu · Chelsea Finn · Stefano Ermon -
2019 Poster: Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction »
Aviral Kumar · Justin Fu · George Tucker · Sergey Levine -
2019 Poster: Unsupervised Curricula for Visual Meta-Reinforcement Learning »
Allan Jabri · Kyle Hsu · Abhishek Gupta · Benjamin Eysenbach · Sergey Levine · Chelsea Finn -
2019 Poster: Approximating the Permanent by Sampling from Adaptive Partitions »
Jonathan Kuck · Tri Dao · Hamid Rezatofighi · Ashish Sabharwal · Stefano Ermon -
2019 Poster: Language as an Abstraction for Hierarchical Deep Reinforcement Learning »
YiDing Jiang · Shixiang (Shane) Gu · Kevin Murphy · Chelsea Finn -
2019 Poster: Compositional Plan Vectors »
Coline Devin · Daniel Geng · Pieter Abbeel · Trevor Darrell · Sergey Levine -
2019 Poster: Verified Uncertainty Calibration »
Ananya Kumar · Percy Liang · Tengyu Ma -
2019 Spotlight: Unsupervised Curricula for Visual Meta-Reinforcement Learning »
Allan Jabri · Kyle Hsu · Abhishek Gupta · Benjamin Eysenbach · Sergey Levine · Chelsea Finn -
2019 Spotlight: Verified Uncertainty Calibration »
Ananya Kumar · Percy Liang · Tengyu Ma -
2019 Poster: Causal Confusion in Imitation Learning »
Pim de Haan · Dinesh Jayaraman · Sergey Levine -
2019 Poster: Generative Modeling by Estimating Gradients of the Data Distribution »
Yang Song · Stefano Ermon -
2019 Poster: Meta-Learning with Implicit Gradients »
Aravind Rajeswaran · Chelsea Finn · Sham Kakade · Sergey Levine -
2019 Poster: When to Trust Your Model: Model-Based Policy Optimization »
Michael Janner · Justin Fu · Marvin Zhang · Sergey Levine -
2019 Poster: Guided Meta-Policy Search »
Russell Mendonca · Abhishek Gupta · Rosen Kralev · Pieter Abbeel · Sergey Levine · Chelsea Finn -
2019 Spotlight: Guided Meta-Policy Search »
Russell Mendonca · Abhishek Gupta · Rosen Kralev · Pieter Abbeel · Sergey Levine · Chelsea Finn -
2019 Oral: Causal Confusion in Imitation Learning »
Pim de Haan · Dinesh Jayaraman · Sergey Levine -
2019 Oral: Generative Modeling by Estimating Gradients of the Data Distribution »
Yang Song · Stefano Ermon -
2019 Poster: Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation »
Colin Wei · Tengyu Ma -
2019 Poster: Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks »
Yuanzhi Li · Colin Wei · Tengyu Ma -
2019 Spotlight: Data-dependent Sample Complexity of Deep Neural Networks via Lipschitz Augmentation »
Colin Wei · Tengyu Ma -
2019 Spotlight: Towards Explaining the Regularization Effect of Initial Large Learning Rate in Training Neural Networks »
Yuanzhi Li · Colin Wei · Tengyu Ma -
2018 : Meta-Learning to Follow Instructions, Examples, and Demonstrations »
Sergey Levine -
2018 : TBA 2 »
Sergey Levine -
2018 : Control as Inference and Soft Deep RL (Sergey Levine) »
Sergey Levine -
2018 Workshop: Relational Representation Learning »
Aditya Grover · Paroma Varma · Frederic Sala · Christopher Ré · Jennifer Neville · Stefano Ermon · Steven Holtzen -
2018 : TBC 9 »
Sergey Levine -
2018 : Stefano Ermon (Stanford University): Weakly Supervised Spatio-temporal Regression »
Stefano Ermon -
2018 Poster: Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models »
Kurtland Chua · Roberto Calandra · Rowan McAllister · Sergey Levine -
2018 Poster: Streamlining Variational Inference for Constraint Satisfaction Problems »
Aditya Grover · Tudor Achim · Stefano Ermon -
2018 Spotlight: Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models »
Kurtland Chua · Roberto Calandra · Rowan McAllister · Sergey Levine -
2018 Poster: Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance »
Neal Jean · Sang Michael Xie · Stefano Ermon -
2018 Poster: Probabilistic Model-Agnostic Meta-Learning »
Chelsea Finn · Kelvin Xu · Sergey Levine -
2018 Poster: Meta-Reinforcement Learning of Structured Exploration Strategies »
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine -
2018 Poster: Multi-Agent Generative Adversarial Imitation Learning »
Jiaming Song · Hongyu Ren · Dorsa Sadigh · Stefano Ermon -
2018 Poster: Visual Reinforcement Learning with Imagined Goals »
Ashvin Nair · Vitchyr Pong · Murtaza Dalal · Shikhar Bahl · Steven Lin · Sergey Levine -
2018 Spotlight: Visual Reinforcement Learning with Imagined Goals »
Ashvin Nair · Vitchyr Pong · Murtaza Dalal · Shikhar Bahl · Steven Lin · Sergey Levine -
2018 Spotlight: Meta-Reinforcement Learning of Structured Exploration Strategies »
Abhishek Gupta · Russell Mendonca · YuXuan Liu · Pieter Abbeel · Sergey Levine -
2018 Poster: Visual Memory for Robust Path Following »
Ashish Kumar · Saurabh Gupta · David Fouhey · Sergey Levine · Jitendra Malik -
2018 Poster: Constructing Unrestricted Adversarial Examples with Generative Models »
Yang Song · Rui Shu · Nate Kushman · Stefano Ermon -
2018 Poster: Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition »
Justin Fu · Avi Singh · Dibya Ghosh · Larry Yang · Sergey Levine -
2018 Oral: Visual Memory for Robust Path Following »
Ashish Kumar · Saurabh Gupta · David Fouhey · Sergey Levine · Jitendra Malik -
2018 Poster: Data-Efficient Hierarchical Reinforcement Learning »
Ofir Nachum · Shixiang (Shane) Gu · Honglak Lee · Sergey Levine -
2018 Poster: Learning a Warping Distance from Unlabeled Time Series Using Sequence Autoencoders »
Abubakar Abid · James Zou -
2018 Poster: Bias and Generalization in Deep Generative Models: An Empirical Study »
Shengjia Zhao · Hongyu Ren · Arianna Yuan · Jiaming Song · Noah Goodman · Stefano Ermon -
2018 Spotlight: Bias and Generalization in Deep Generative Models: An Empirical Study »
Shengjia Zhao · Hongyu Ren · Arianna Yuan · Jiaming Song · Noah Goodman · Stefano Ermon -
2018 Poster: Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior »
Sid Reddy · Anca Dragan · Sergey Levine -
2018 Poster: Amortized Inference Regularization »
Rui Shu · Hung Bui · Shengjia Zhao · Mykel J Kochenderfer · Stefano Ermon -
2017 : Generative Adversarial Imitation Learning, Stefano Ermon, Stanford »
Stefano Ermon -
2017 Workshop: Workshop on Meta-Learning »
Roberto Calandra · Frank Hutter · Hugo Larochelle · Sergey Levine -
2017 : Stefano Ermon (Stanford): Measuring Progress Towards Sustainable Development Goals with Machine Learning »
Stefano Ermon -
2017 Poster: EX2: Exploration with Exemplar Models for Deep Reinforcement Learning »
Justin Fu · John Co-Reyes · Sergey Levine -
2017 Spotlight: EX2: Exploration with Exemplar Models for Deep Reinforcement Learning »
Justin Fu · John Co-Reyes · Sergey Levine -
2017 Demonstration: Deep Robotic Learning using Visual Imagination and Meta-Learning »
Chelsea Finn · Frederik Ebert · Tianhe Yu · Annie Xie · Sudeep Dasari · Pieter Abbeel · Sergey Levine -
2017 Poster: A-NICE-MC: Adversarial Training for MCMC »
Jiaming Song · Shengjia Zhao · Stefano Ermon -
2017 Poster: InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations »
Yunzhu Li · Jiaming Song · Stefano Ermon -
2017 Poster: Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning »
Shixiang (Shane) Gu · Timothy Lillicrap · Richard Turner · Zoubin Ghahramani · Bernhard Schölkopf · Sergey Levine -
2017 Poster: Neural Variational Inference and Learning in Undirected Graphical Models »
Volodymyr Kuleshov · Stefano Ermon -
2016 Workshop: Deep Learning for Action and Interaction »
Chelsea Finn · Raia Hadsell · David Held · Sergey Levine · Percy Liang -
2016 : Sergey Levine (University of California, Berkeley) »
Sergey Levine -
2016 Poster: Solving Marginal MAP Problems with NP Oracles and Parity Constraints »
Yexiang Xue · zhiyuan li · Stefano Ermon · Carla Gomes · Bart Selman -
2016 Poster: Generative Adversarial Imitation Learning »
Jonathan Ho · Stefano Ermon -
2016 Poster: Variational Bayes on Monte Carlo Steroids »
Aditya Grover · Stefano Ermon -
2016 Poster: Adaptive Concentration Inequalities for Sequential Decision Problems »
Shengjia Zhao · Enze Zhou · Ashish Sabharwal · Stefano Ermon -
2016 Poster: Value Iteration Networks »
Aviv Tamar · Sergey Levine · Pieter Abbeel · YI WU · Garrett Thomas -
2016 Oral: Value Iteration Networks »
Aviv Tamar · Sergey Levine · Pieter Abbeel · YI WU · Garrett Thomas -
2015 : Deep Robotic Learning »
Sergey Levine -
2014 Workshop: Novel Trends and Applications in Reinforcement Learning »
Csaba Szepesvari · Marc Deisenroth · Sergey Levine · Pedro Ortega · Brian Ziebart · Emma Brunskill · Naftali Tishby · Gerhard Neumann · Daniel Lee · Sridhar Mahadevan · Pieter Abbeel · David Silver · Vicenç Gómez -
2014 Poster: Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics »
Sergey Levine · Pieter Abbeel -
2014 Spotlight: Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics »
Sergey Levine · Pieter Abbeel -
2013 Poster: Variational Policy Search via Trajectory Optimization »
Sergey Levine · Vladlen Koltun -
2013 Poster: Embed and Project: Discrete Sampling with Universal Hashing »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2012 Poster: Density Propagation and Improved Bounds on the Partition Function »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2011 Poster: Accelerated Adaptive Markov Chain for Partition Function Computation »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2011 Spotlight: Accelerated Adaptive Markov Chain for Partition Function Computation »
Stefano Ermon · Carla Gomes · Ashish Sabharwal · Bart Selman -
2010 Poster: Feature Construction for Inverse Reinforcement Learning »
Sergey Levine · Zoran Popovic · Vladlen Koltun