← Authors

Sergey Levine

362 papers · 2010–2026 · 14 conferences · across top CS/AI conferences

Achievements

πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (14) πŸƒ Academic Marathon (15) 🌍 Conference Polyglot (13) 🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (44) 🌟 Keyword Trendsetter Combo (15) 🏠 Conference Loyalist (82) πŸ‘‘ Domain Dominant (52) 🧬 Topic Evolution πŸ”¬ Deep Specialist (20) 🌱 Topic Pioneer πŸ† Keyword Champion (8) 🀝 Dynamic Duo (90) πŸ‘‘ Triple Crown πŸ‘₯ Mega-Team (98) πŸ† Grand Slam ⚑ Prolific Year (46) ❓ The Questioner (9) πŸ”₯ Unstoppable (13) πŸ—ƒοΈ Keyword Collector (213) πŸš€ Conference Pioneer πŸ’Ž Century Club (361) πŸ“ˆ Trend Setter

Conferences

ICLR (90) NIPS (82) ICML (75) CORL (67) RSS (30) CVPR (4) NAACL (4) ICCV (3) L4DC (2) AAAI (1) AISTATS (1) ECCV (1) IJCAI (1) JMLR (1)

Top co-authors

Chelsea Finn (90) Aviral Kumar (45) Pieter Abbeel (36) Karol Hausman (29) Abhishek Gupta (27) Benjamin Eysenbach (27) Ted Xiao (18) Quan Vuong (17) Karl Pertsch (17) Yevgen Chebotar (16)

Research topics

Reinforcement Learning (4) Applications (1) Robotics (1) Systems (1)

Keywords

reinforcement learning (54) offline reinforcement learning (30) deep reinforcement learning (26) imitation learning (26) representation learning (24) robotic manipulation (22) model-based reinforcement learning (16) sample efficiency (16) multi-task learning (12) distribution shift (12) policy learning (12) continuous control (11) off-policy learning (11) self-supervised learning (10) policy optimization (10) robot manipulation (10) goal-conditioned policy (10) few-shot learning (9) reward function (9) value function (9)

Papers

Cliqueformer: Model-Based Optimization with Structured Transformers AAAI 2026
Proposer-Agent-Evaluator (PAE): Autonomous Skill Discovery For Foundation Model Internet Agents ICML 2025
Leveraging Skills from Unlabeled Prior Data for Efficient Online Exploration ICML 2025
Behavioral Exploration: Learning to Explore via In-Context Adaptation ICML 2025
Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design ICML 2025
Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models ICML 2025
Scaling Test-Time Compute Without Verification or RL is Suboptimal ICML 2025
Value-Based Deep RL Scales Predictably ICML 2025
Reflective Planning: Vision-Language Models for Multi-Stage Long-Horizon Robotic Manipulation CORL 2025
AutoEval: Autonomous Evaluation of Generalist Robot Manipulation Policies in the Real World CORL 2025
Training Strategies for Efficient Embodied Reasoning CORL 2025
RoboArena: Distributed Real-World Evaluation of Generalist Robot Policies CORL 2025
Steering Your Diffusion Policy with Latent Space Reinforcement Learning CORL 2025
$\pi_0.5$: a Vision-Language-Action Model with Open-World Generalization CORL 2025
Flow Q-Learning ICML 2025
What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning? ICML 2025
Adding Conditional Control to Diffusion Models with Reinforcement Learning ICLR 2025
Prioritized Generative Replay ICLR 2025
Digi-Q: Learning VLM Q-Value Functions for Training Device-Control Agents ICLR 2025
OGBench: Benchmarking Offline Goal-Conditioned RL ICLR 2025
One Step Diffusion via Shortcut Models ICLR 2025
Language Guided Skill Discovery ICLR 2025
Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design ICLR 2025
Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning ICLR 2025
RLDG: Robotic Generalist Policy Distillation via Reinforcement Learning RSS 2025
FAST: Efficient Action Tokenization for Vision-Language-Action Models RSS 2025
Ο€β‚€: A Vision-Language-Action Flow Model for General Robot Control RSS 2025
Efficient Online Reinforcement Learning Fine-Tuning Need Not Retain Offline Data ICLR 2025
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training ICML 2025
Unfamiliar Finetuning Examples Control How Language Models Hallucinate NAACL 2025
LMRL Gym: Benchmarks for Multi-Turn Reinforcement Learning with Language Models ICML 2025
Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance CORL 2024
Autonomous Improvement of Instruction Following Skills via Foundation Models CORL 2024
Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs CORL 2024
Evaluating Real-World Robot Manipulation Policies in Simulation CORL 2024
Robotic Control via Embodied Chain-of-Thought Reasoning CORL 2024
OpenVLA: An Open-Source Vision-Language-Action Model CORL 2024
Policy Adaptation via Language Optimization: Decomposing Tasks for Few-Shot Imitation CORL 2024
Lifelong Autonomous Improvement of Navigation Foundation Models in the Wild CORL 2024
LeLaN: Learning A Language-Conditioned Navigation Policy from In-the-Wild Video CORL 2024
Scaling Cross-Embodied Learning: One Policy for Manipulation, Navigation, Locomotion and Aviation CORL 2024
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset RSS 2024
Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation RSS 2024
DigiRL: Training In-The-Wild Device-Control Agents with Autonomous Reinforcement Learning NIPS 2024
Octo: An Open-Source Generalist Robot Policy RSS 2024
Inference via Interpolation: Contrastive Representations Provably Enable Planning and Inference NIPS 2024
Learning to Assist Humans without Inferring Rewards NIPS 2024
Is Value Learning Really the Main Bottleneck in Offline RL? NIPS 2024
Designing Cell-Type-Specific Promoter Sequences Using Conservative Model-Based Optimization NIPS 2024
Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning NIPS 2024
Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models NIPS 2024
SELFI: Autonomous Self-Improvement with RL for Vision-Based Navigation around People CORL 2024
RACER: Epistemic Risk-Sensitive RL Enables Fast Driving with Fewer Crashes RSS 2024
MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting RSS 2024
Yell At Your Robot: Improving On-the-Fly from Language Corrections RSS 2024
ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL ICML 2024
Learning to Explore in POMDPs with Informational Rewards ICML 2024
Feedback Efficient Online Fine-Tuning of Diffusion Models ICML 2024
Prompting is a Double-Edged Sword: Improving Worst-Group Robustness of Foundation Models ICML 2024
Foundation Policies with Hilbert Representations ICML 2024
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs ICML 2024
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making ICML 2024
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator ICML 2024
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings ICML 2024
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL ICML 2024
Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features ICLR 2024
Deep Neural Networks Tend To Extrapolate Predictably ICLR 2024
METRA: Scalable Unsupervised RL with Metric-Aware Abstraction ICLR 2024
The False Promise of Imitating Proprietary Language Models ICLR 2024
RLIF: Interactive Imitation Learning as Reinforcement Learning ICLR 2024
Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data ICLR 2024
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity ICLR 2024
Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models ICLR 2024
Training Diffusion Models with Reinforcement Learning ICLR 2024
Functional Graphical Models: Structure Enables Offline Data-Driven Optimization AISTATS 2024
Offline RL for Natural Language Generation with Implicit Language Q Learning ICLR 2023
ReDS: Offline RL With Heteroskedastic Datasets via Support Constraints NIPS 2023
HIQL: Offline Goal-Conditioned RL with Latent States as Actions NIPS 2023
Learning to Influence Human Behavior with Offline Reinforcement Learning NIPS 2023
Ignorance is Bliss: Robust Control via Information Gating NIPS 2023
Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents NIPS 2023
Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning NIPS 2023
Accelerating Exploration with Unlabeled Prior Data NIPS 2023
ViNT: A Foundation Model for Visual Navigation CORL 2023
Action-Quantized Offline Reinforcement Learning for Robotic Skill Learning CORL 2023
BridgeData V2: A Dataset for Robot Learning at Scale CORL 2023
REBOOT: Reuse Data for Bootstrapping Efficient Real-World Dexterous Manipulation CORL 2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control CORL 2023
Navigation with Large Language Models: Semantic Guesswork as a Heuristic for Planning CORL 2023
FastRLAP: A System for Learning High-Speed Driving via Deep RL and Autonomous Practicing CORL 2023
Goal Representations for Instruction Following: A Semi-Supervised Language Interface to Control CORL 2023
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions CORL 2023
Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement ICLR 2023
Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts ICLR 2023
Efficient Deep Reinforcement Learning Requires Regulating Overfitting ICLR 2023
Simplifying Model-based RL: Learning Representations, Latent-space Models, and Policies with One Objective ICLR 2023
Offline Q-learning on Diverse Multi-Task Data Both Scales And Generalizes ICLR 2023
Confidence-Conditioned Value Functions for Offline Reinforcement Learning ICLR 2023
Efficient Online Reinforcement Learning with Offline Data ICML 2023
PaLM-E: An Embodied Multimodal Language Model ICML 2023
A Connection between One-Step RL and Critic Regularization in Reinforcement Learning ICML 2023
Reinforcement Learning from Passive Data via Latent Intentions ICML 2023
Understanding the Complexity Gains of Single-Task RL with a Curriculum ICML 2023
Predictable MDP Abstraction for Unsupervised Model-Based RL ICML 2023
Jump-Start Reinforcement Learning ICML 2023
Adversarial Policies Beat Superhuman Go AIs ICML 2023
Contrastive Example-Based Control L4DC 2023
Multi-Task Imitation Learning for Linear Dynamical Systems L4DC 2023
Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware RSS 2023
Pre-Training for Robots: Offline RL Enables Learning New Tasks in a Handful of Trials RSS 2023
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators RSS 2023
RT-1: Robotics Transformer for Real-World Control at Scale RSS 2023
Robotic Skill Acquisition via Instruction Augmentation with Vision-Language Models RSS 2023
Learning and Adapting Agile Locomotion Skills by Transferring Experience RSS 2023
Robust and Versatile Bipedal Jumping Control through Reinforcement Learning RSS 2023
Demonstrating A Walk in the Park: Learning to Walk in 20 Minutes With Model-Free Reinforcement Learning RSS 2023
Maximum Entropy RL (Provably) Solves Some Robust RL Problems ICLR 2022
MEMO: Test Time Robustness via Adaptation and Augmentation NIPS 2022
ViKiNG: Vision-Based Kilometer-Scale Navigation with Geographic Hints RSS 2022
Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets RSS 2022
Contrastive Learning as Goal-Conditioned Reinforcement Learning NIPS 2022
Object Representations as Fixed Points: Training Iterative Refinement Algorithms with Implicit Differentiation NIPS 2022
First Contact: Unsupervised Human-Machine Co-Adaptation via Mutual Information Maximization NIPS 2022
Generalization with Lossy Affordances: Leveraging Broad Offline Data for Learning Visuomotor Tasks CORL 2022
Distributionally Adaptive Meta Reinforcement Learning NIPS 2022
Mismatched No More: Joint Model-Policy Optimization for Model-Based RL NIPS 2022
Adversarial Unlearning: Reducing Confidence Along Adversarial Directions NIPS 2022
Unpacking Reward Shaping: Understanding the Benefits of Reward Engineering on Sample Complexity NIPS 2022
You Only Live Once: Single-Life Reinforcement Learning NIPS 2022
Data-Driven Offline Decision-Making via Invariant Representation Learning NIPS 2022
Is Anyone There? Learning a Planner Contingent on Perceptual Uncertainty CORL 2022
Don’t Start From Scratch: Leveraging Prior Data to Automate Robotic Reinforcement Learning CORL 2022
Inner Monologue: Embodied Reasoning through Planning with Language Models CORL 2022
GenLoco: Generalized Locomotion Controllers for Quadrupedal Robots CORL 2022
Context-Aware Language Modeling for Goal-Oriented Dialogue Systems NAACL 2022
Offline Reinforcement Learning for Visual Navigation CORL 2022
Imitating Past Successes can be Very Suboptimal NIPS 2022
TRAIL: Near-Optimal Imitation Learning with Suboptimal Data ICLR 2022
Autonomous Reinforcement Learning: Formalism and Benchmarking ICLR 2022
Information Prioritization through Empowerment in Visual Model-based RL ICLR 2022
RvS: What is Essential for Offline RL via Supervised Learning? ICLR 2022
C-Planning: An Automatic Curriculum for Learning Goal-Reaching Tasks ICLR 2022
CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning NAACL 2022
How to Leverage Unlabeled Data in Offline Reinforcement Learning ICML 2022
Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization ICML 2022
Do As I Can, Not As I Say: Grounding Language in Robotic Affordances CORL 2022
LM-Nav: Robotic Navigation with Large Pre-Trained Models of Language, Vision, and Action CORL 2022
Offline Meta-Reinforcement Learning with Online Self-Supervision ICML 2022
Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control ICML 2022
Should I Run Offline Reinforcement Learning or Behavioral Cloning? ICLR 2022
Planning with Diffusion for Flexible Behavior Synthesis ICML 2022
Bisimulation Makes Analogies in Goal-Conditioned Reinforcement Learning ICML 2022
Offline RL Policies Should Be Trained to be Adaptive ICML 2022
Extending the WILDS Benchmark for Unsupervised Adaptation ICLR 2022
The Information Geometry of Unsupervised Reinforcement Learning ICLR 2022
DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization ICLR 2022
Offline Reinforcement Learning with Implicit Q-Learning ICLR 2022
CoMPS: Continual Meta Policy Search ICLR 2022
DASCO: Dual-Generator Adversarial Support Constrained Offline Reinforcement Learning NIPS 2022
Value Function Spaces: Skill-Centric State Abstractions for Long-Horizon Reasoning ICLR 2022
Data-Driven Offline Optimization for Architecting Hardware Accelerators ICLR 2022
Learning Invariant Representations for Reinforcement Learning without Reconstruction ICLR 2021
SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments ICLR 2021
Learning to Reach Goals via Iterated Supervised Learning ICLR 2021
Recurrent Independent Mechanisms ICLR 2021
Model-Based Visual Planning with Self-Supervised Functional Distances ICLR 2021
Implicit Under-Parameterization Inhibits Data-Efficient Deep Reinforcement Learning ICLR 2021
Autonomous Reinforcement Learning via Subgoal Curricula NIPS 2021
Fully Autonomous Real-World Reinforcement Learning with Applications to Mobile Manipulation CORL 2021
Adaptive Risk Minimization: Learning to Adapt to Domain Shift NIPS 2021
COMBO: Conservative Offline Model-Based Policy Optimization NIPS 2021
Robust Predictable Control NIPS 2021
Pragmatic Image Compression for Human-in-the-Loop Decision-Making NIPS 2021
Which Mutual-Information Representation Learning Objectives are Sufficient for Control? NIPS 2021
Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability NIPS 2021
Amortized Conditional Normalized Maximum Likelihood: Reliable Out of Distribution Uncertainty Estimation ICML 2021
Conservative Objective Models for Effective Offline Model-Based Optimization ICML 2021
Model-Based Reinforcement Learning via Latent-Space Collocation ICML 2021
Simple and Effective VAE Training with Calibrated Decoders ICML 2021
Emergent Social Learning via Multi-agent Reinforcement Learning ICML 2021
Offline Meta-Reinforcement Learning with Advantage Weighting ICML 2021
MURAL: Meta-Learning Uncertainty-Aware Rewards for Outcome-Driven Reinforcement Learning ICML 2021
WILDS: A Benchmark of in-the-Wild Distribution Shifts ICML 2021
Policy Information Capacity: Information-Theoretic Measure for Task Complexity in Deep Reinforcement Learning ICML 2021
PsiPhi-Learning: Reinforcement Learning with Demonstrations using Successor Features and Inverse Temporal Difference Learning ICML 2021
Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning ICML 2021
Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills ICML 2021
Modularity in Reinforcement Learning via Algorithmic Independence in Credit Assignment ICML 2021
Bayesian Adaptation for Covariate Shift NIPS 2021
Offline Reinforcement Learning as One Big Sequence Modeling Problem NIPS 2021
Information is Power: Intrinsic Control via Information Capture NIPS 2021
Conservative Data Sharing for Multi-Task Offline Reinforcement Learning NIPS 2021
Replacing Rewards with Examples: Example-Based Policy Search via Recursive Classification NIPS 2021
Outcome-Driven Reinforcement Learning via Variational Inference NIPS 2021
Understanding the World Through Action CORL 2021
Hierarchically Integrated Models: Learning to Navigate from Heterogeneous Robots CORL 2021
AW-Opt: Learning Robotic Skills with Imitation andReinforcement at Scale CORL 2021
BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning CORL 2021
Rapid Exploration for Open-World Navigation with Latent Goal Models CORL 2021
Scaling Up Multi-Task Robotic Reinforcement Learning CORL 2021
A Workflow for Offline Model-Free Robotic Reinforcement Learning CORL 2021
Benchmarks for Deep Off-Policy Evaluation ICLR 2021
Factorizing Declarative and Procedural Knowledge in Structured, Dynamical Environments ICLR 2021
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation ICLR 2021
X2T: Training an X-to-Text Typing Interface with Online Learning from User Feedback ICLR 2021
C-Learning: Learning to Achieve Goals via Recursive Classification ICLR 2021
Off-Dynamics Reinforcement Learning: Training for Transfer with Domain Classifiers ICLR 2021
Conservative Safety Critics for Exploration ICLR 2021
OPAL: Offline Primitive Discovery for Accelerating Offline Reinforcement Learning ICLR 2021
Evolving Reinforcement Learning Algorithms ICLR 2021
Parrot: Data-Driven Behavioral Priors for Reinforcement Learning ICLR 2021
Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions ICML 2020
RL-CycleGAN: Reinforcement Learning Aware Simulation-to-Real CVPR 2020
Learning Predictive Models from Observation and Interaction ECCV 2020
The Ingredients of Real World Robotic Reinforcement Learning ICLR 2020
Model Based Reinforcement Learning for Atari ICLR 2020
Thinking While Moving: Deep Reinforcement Learning with Concurrent Control ICLR 2020
Deep Imitative Models for Flexible Inference, Planning, and Control ICLR 2020
Dynamics-Aware Unsupervised Discovery of Skills ICLR 2020
Dynamical Distance Learning for Semi-Supervised and Unsupervised Skill Discovery ICLR 2020
Meta-Learning without Memorization ICLR 2020
VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation ICLR 2020
Adversarial Policies: Attacking Deep Reinforcement Learning ICLR 2020
Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards ICLR 2020
Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives ICLR 2020
The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget ICLR 2020
SQIL: Imitation Learning via Reinforcement Learning with Sparse Rewards ICLR 2020
AVID: Learning Multi-Stage Tasks via Pixel-Level Translation of Human Videos RSS 2020
Emergent Real-World Robotic Skills via Unsupervised Off-Policy Reinforcement Learning RSS 2020
Learning Agile Robotic Locomotion Skills by Imitating Animals RSS 2020
DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction NIPS 2020
Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors NIPS 2020
Rewriting History with Inverse RL: Hindsight Inference for Policy Improvement NIPS 2020
MOPO: Model-based Offline Policy Optimization NIPS 2020
Emergent Complexity and Zero-shot Transfer via Unsupervised Environment Design NIPS 2020
One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL NIPS 2020
Gradient Surgery for Multi-Task Learning NIPS 2020
Model Inversion Networks for Model-Based Optimization NIPS 2020
Continual Learning of Control Primitives : Skill Discovery via Reset-Games NIPS 2020
Gamma-Models: Generative Temporal Difference Learning for Infinite-Horizon Prediction NIPS 2020
Can Autonomous Vehicles Identify, Recover From, and Adapt to Distribution Shifts? ICML 2020
Skew-Fit: State-Covering Self-Supervised Reinforcement Learning ICML 2020
Learning Human Objectives by Evaluating Hypothetical Behavior ICML 2020
Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings ICML 2020
Conservative Q-Learning for Offline Reinforcement Learning NIPS 2020
Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model NIPS 2020
Inverting the Pose Forecasting Pipeline with SPF2: Sequential Pointcloud Forecasting for Sequential Pose Forecasting CORL 2020
Reinforcement Learning with Videos: Combining Offline Observations with Interaction CORL 2020
Assisted Perception: Optimizing Observations to Communicate State CORL 2020
Learning to Walk in the Real World with Minimal Human Effort CORL 2020
MELD: Meta-Reinforcement Learning from Images via Latent State Models CORL 2020
Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning CORL 2020
Chaining Behaviors from Data with Model-Free Reinforcement Learning CORL 2020
Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning ICLR 2019
Near-Optimal Representation Learning for Hierarchical Reinforcement Learning ICLR 2019
End-To-End Robotic Reinforcement Learning without Reward Engineering RSS 2019
Contextual Imagined Goals for Self-Supervised Robotic Learning CORL 2019
Learning to Walk Via Deep Reinforcement Learning RSS 2019
Wasserstein Dependency Measure for Representation Learning NIPS 2019
Unsupervised Curricula for Visual Meta-Reinforcement Learning NIPS 2019
Guided Meta-Policy Search NIPS 2019
Planning with Goal-Conditioned Policies NIPS 2019
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction NIPS 2019
Off-Policy Evaluation via Off-Policy Classification NIPS 2019
MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies NIPS 2019
Causal Confusion in Imitation Learning NIPS 2019
When to Trust Your Model: Model-Based Policy Optimization NIPS 2019
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning NIPS 2019
Meta-Learning with Implicit Gradients NIPS 2019
Compositional Plan Vectors NIPS 2019
Improvisation through Physical Understanding: Using Novel Objects As Tools with Visual Foresight RSS 2019
Learning Latent Plans from Play CORL 2019
Deep Dynamics Models for Learning Dexterous Manipulation CORL 2019
Entity Abstraction in Visual Model-Based Reinforcement Learning CORL 2019
Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow ICLR 2019
Learning Actionable Representations with Goal Conditioned Policies ICLR 2019
Time-Agnostic Prediction: Predicting Predictable Video Frames ICLR 2019
Recall Traces: Backtracking Models for Efficient Reinforcement Learning ICLR 2019
Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL ICLR 2019
Automatically Composing Representation Transformations as a Means for Generalization ICLR 2019
Guiding Policies with Language via Meta-Learning ICLR 2019
Reasoning About Physical Interactions with Object-Oriented Prediction and Planning ICLR 2019
ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots CORL 2019
Online Meta-Learning ICML 2019
Diagnosing Bottlenecks in Deep Q-learning Algorithms ICML 2019
EMI: Exploration with Mutual Information ICML 2019
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables ICML 2019
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning ICML 2019
SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning ICML 2019
PRECOG: PREdiction Conditioned on Goals in Visual Multi-Agent Settings ICCV 2019
Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning CORL 2019
Relay Policy Learning: Solving Long-Horizon Tasks via Imitation and Reinforcement Learning CORL 2019
Sim-To-Real via Sim-To-Sim: Data-Efficient Robotic Grasping via Randomized-To-Canonical Adaptation Networks CVPR 2019
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following ICLR 2019
RoboNet: Large-Scale Multi-Robot Learning CORL 2019
InfoBot: Transfer and Exploration via the Information Bottleneck ICLR 2019
Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning ICLR 2019
Unsupervised Learning via Meta-Learning ICLR 2019
Diversity is All You Need: Learning Skills without a Reward Function ICLR 2019
Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation CORL 2018
Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings ICML 2018
Latent Space Policies for Hierarchical Reinforcement Learning ICML 2018
Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor ICML 2018
Regret Minimization for Partially Observable Deep Reinforcement Learning ICML 2018
Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control ICML 2018
The Mirage of Action-Dependent Baselines in Reinforcement Learning ICML 2018
One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning RSS 2018
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models NIPS 2018
Divide-and-Conquer Reinforcement Learning ICLR 2018
Temporal Difference Models: Model-Free Deep RL for Model-Based Control ICLR 2018
Learning Robust Rewards with Adverserial Inverse Reinforcement Learning ICLR 2018
Recasting Gradient-Based Meta-Learning as Hierarchical Bayes ICLR 2018
Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning ICLR 2018
Stochastic Variational Video Prediction ICLR 2018
Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm ICLR 2018
Sim2Real Viewpoint Invariant Visual Servoing by Recurrent Control CVPR 2018
Data-Efficient Hierarchical Reinforcement Learning NIPS 2018
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition NIPS 2018
Probabilistic Model-Agnostic Meta-Learning NIPS 2018
Visual Reinforcement Learning with Imagined Goals NIPS 2018
Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior NIPS 2018
Visual Memory for Robust Path Following NIPS 2018
Meta-Reinforcement Learning of Structured Exploration Strategies NIPS 2018
Learning with Latent Language NAACL 2018
Few-Shot Goal Inference for Visuomotor Learning and Planning CORL 2018
Grasp2Vec: Learning Object Representations from Self-Supervised Grasping CORL 2018
Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation CORL 2018
Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning CORL 2018
Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations RSS 2018
Shared Autonomy via Deep Reinforcement Learning RSS 2018
The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes? CORL 2017
Self-Supervised Visual Planning with Temporal Skip Connections CORL 2017
One-Shot Visual Imitation Learning via Meta-Learning CORL 2017
Modular Multitask Reinforcement Learning with Policy Sketches ICML 2017
End-to-End Learning of Semantic Grasping CORL 2017
GPLAC: Generalizing Vision-Based Robotic Skills Using Weakly Labeled Images ICCV 2017
CAD2RL: Real Single-Image Flight Without a Single Real Image RSS 2017
Unsupervised Perceptual Rewards for Imitation Learning RSS 2017
Reinforcement Learning with Deep Energy-Based Policies ICML 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks ICML 2017
Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning ICML 2017
Value Iteration Networks IJCAI 2017
Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning NIPS 2017
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning NIPS 2017
Cognitive Mapping and Planning for Visual Navigation CVPR 2017
Learning Robotic Manipulation of Granular Media CORL 2017
Learning to Poke by Poking: Experiential Learning of Intuitive Physics NIPS 2016
Unsupervised Learning for Physical Interaction through Video Prediction NIPS 2016
Continuous Deep Q-Learning with Model-based Acceleration ICML 2016
Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization ICML 2016
End-to-End Training of Deep Visuomotor Policies JMLR 2016
Backprop KF: Learning Discriminative Deterministic State Estimators NIPS 2016
Guided Policy Search via Approximate Mirror Descent NIPS 2016
Value Iteration Networks NIPS 2016
Recurrent Network Models for Human Dynamics ICCV 2015
Trust Region Policy Optimization ICML 2015
Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics NIPS 2014
Learning Complex Neural Network Policies with Trajectory Optimization ICML 2014
Guided Policy Search ICML 2013
Variational Policy Search via Trajectory Optimization NIPS 2013
Nonlinear Inverse Reinforcement Learning with Gaussian Processes NIPS 2011
Feature Construction for Inverse Reinforcement Learning NIPS 2010