Chelsea Finn

James Harrison

CoRR, 2024

AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents.

[BibT_eX]

[DOI]

CoRR, 2024

AutoFT: Robust Fine-Tuning by Optimizing Hyperparameters on OOD Data.

[BibT_eX]

[DOI]

CoRR, 2024

Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation.

[BibT_eX]

[DOI]

Zipeng Fu

Tony Z. Zhao

CoRR, 2024

Clarify: Improving Model Robustness With Natural Language Corrections.

[BibT_eX]

[DOI]

Proceedings of the 37th Annual ACM Symposium on User Interface Software and Technology, 2024

A Fast and Accurate Machine Learning Autograder for the Breakout Assignment.

[BibT_eX]

[DOI]

Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Policy Architectures for Compositional Generalization in Control.

[BibT_eX]

Proceedings of the 1st Reinforcement Learning Conference, 2024

D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning.

[BibT_eX]

Philippe Hansen-Estruch

Proceedings of the 1st Reinforcement Learning Conference, 2024

Efficient imitation learning with conservative world models.

[BibT_eX]

[DOI]

Proceedings of the 6th Annual Learning for Dynamics & Control Conference, 2024

Robot Fine-Tuning Made Easy: Pre-Training Rewards and Policies for Autonomous Real-World Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration.

[BibT_eX]

[DOI]

Henrik I. Christensen

Nur Muhammad (Mahi) Shafiullah

Lawrence Yunliang Chen

Roberto Martín-Martín

Subramanian Ramamoorthy

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Learning to Explore in POMDPs with Informational Rewards.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

RLVF: Learning from Verbal Feedback without Overgeneralization.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning.

[BibT_eX]

[DOI]

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Improving Domain Generalization with Domain Relations.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Fine-Tuning Language Models for Factuality.

[BibT_eX]

[DOI]

Katherine Tian

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Language Model Detectors Are Easily Optimized Against.

[BibT_eX]

[DOI]

Stefano Ermon

Proceedings of the Twelfth International Conference on Learning Representations, 2024

An Emulator for Fine-tuning Large Language Models using Small Language Models.

[BibT_eX]

[DOI]

Montserrat Gonzalez Arenas

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches.

[BibT_eX]

[DOI]

Kanishka Rao

Wenhao Yu

Chuyuan Fu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Calibrating Language Models with Adaptive Temperature Scaling.

[BibT_eX]

[DOI]

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

PIGEON: Predicting Image Geolocations.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Disentangling Length from Quality in Direct Preference Optimization.

[BibT_eX]

[DOI]

Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023

Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2023

What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?

[BibT_eX]

[DOI]

CoRR, 2023

Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment.

[BibT_eX]

[DOI]

CoRR, 2023

Contrastive Preference Learning: Learning from Human Feedback without RL.

[BibT_eX]

[DOI]

CoRR, 2023

Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models.

[BibT_eX]

[DOI]

CoRR, 2023

Open X-Embodiment: Robotic Learning Datasets and RT-X Models.

[BibT_eX]

[DOI]

CoRR, 2023

Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias.

[BibT_eX]

[DOI]

CoRR, 2023

Giving Robots a Hand: Learning Generalizable Manipulation with Eye-in-Hand Human Video Demonstrations.

[BibT_eX]

[DOI]

Moo Jin Kim

Jiajun Wu

CoRR, 2023

Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts.

[BibT_eX]

[DOI]

CoRR, 2023

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning.

[BibT_eX]

[DOI]

CoRR, 2023

Open-World Object Manipulation using Pre-trained Vision-Language Models.

[BibT_eX]

[DOI]

Austin Stone

Ted Xiao

Yao Lu

CoRR, 2023

Permutation Equivariant Neural Functionals.

[BibT_eX]

[DOI]

CoRR, 2023

Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.

[BibT_eX]

[DOI]

CoRR, 2023

Leveraging Domain Relations for Domain Generalization.

[BibT_eX]

[DOI]

CoRR, 2023

A Survey of Meta-Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2023

Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Pre-Training for Robots: Offline RL Enables Learning New Tasks in a Handful of Trials.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Language-Driven Representation Learning for Robotics.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

RT-1: Robotics Transformer for Real-World Control at Scale.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Neural Functional Transformers.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Permutation Equivariant Neural Functionals.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RoboCLIP: One Demonstration is Enough to Learn Robot Policies.

[BibT_eX]

[DOI]

Sumedh Sontakke

Jesse Zhang

Sébastien M. R. Arnold

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Direct Preference Optimization: Your Language Model is Secretly a Reward Model.

[BibT_eX]

[DOI]

Rafael Rafailov

Archit Sharma

Stefano Ermon

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Disentanglement via Latent Quantization.

[BibT_eX]

[DOI]

Kyle Hsu

William Dorrell

James C. R. Whittington

Jiajun Wu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Supervised Pretraining Can Learn In-Context Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Contrastive Example-Based Control.

[BibT_eX]

[DOI]

Proceedings of the Learning for Dynamics and Control Conference, 2023

Train Offline, Test Online: A Real Robot Learning Benchmark.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Robotics and Automation, 2023

DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature.

[BibT_eX]

[DOI]

Yoonho Lee

Alexander Khazatsky

Proceedings of the International Conference on Machine Learning, 2023

Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2023

A Control-Centric Benchmark for Video Prediction.

[BibT_eX]

[DOI]

Stephen Tian

Jiajun Wu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement.

[BibT_eX]

[DOI]

Yoonho Lee

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Just Ask for Calibration: Strategies for Eliciting Calibrated Confidence Scores from Language Models Fine-Tuned with Human Feedback.

[BibT_eX]

[DOI]

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Meta-Learning Online Adaptation of Language Models.

[BibT_eX]

[DOI]

Nathan Hu

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesis.

[BibT_eX]

[DOI]

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2023

Robot Parkour Learning.

[BibT_eX]

[DOI]

Ziwen Zhuang

Zipeng Fu

Jianren Wang

Christopher G. Atkeson

Sören Schwertfeger

Hang Zhao

Proceedings of the Conference on Robot Learning, 2023

Polybot: Training One Policy Across Robots While Embracing Variability.

[BibT_eX]

[DOI]

Jonathan Heewon Yang

Dorsa Sadigh

Proceedings of the Conference on Robot Learning, 2023

BridgeData V2: A Dataset for Robot Learning at Scale.

[BibT_eX]

[DOI]

Philippe Hansen-Estruch

Proceedings of the Conference on Robot Learning, 2023

Open-World Object Manipulation using Pre-Trained Vision-Language Models.

[BibT_eX]

[DOI]

Austin Stone

Ted Xiao

Yao Lu

Proceedings of the Conference on Robot Learning, 2023

Waypoint-Based Imitation Learning for Robotic Manipulation.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2023

Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2023

MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2023

Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2023

Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models.

[BibT_eX]

[DOI]

Peter Henderson

Dan Jurafsky

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 2023

2022

Training and Evaluation of Deep Policies Using Reinforcement Learning and Generative Models.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2022

Knowledge-Driven New Drug Recommendation.

[BibT_eX]

[DOI]

CoRR, 2022

Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials.

[BibT_eX]

[DOI]

CoRR, 2022

Learning to Reason With Relational Abstractions.

[BibT_eX]

[DOI]

CoRR, 2022

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

[BibT_eX]

[DOI]

CoRR, 2022

Latent-Variable Advantage-Weighted Policy Optimization for Offline RL.

[BibT_eX]

[DOI]

CoRR, 2022

Diversify and Disambiguate: Learning From Underspecified Data.

[BibT_eX]

[DOI]

Yoonho Lee

CoRR, 2022

Fully Online Meta-Learning Without Task Boundaries.

[BibT_eX]

[DOI]

Jathushan Rajasegaran

CoRR, 2022

Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

Play it by Ear: Learning Skills amidst Occlusion through Audio-Visual Imitation Learning.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

MEMO: Test Time Robustness via Adaptation and Augmentation.

[BibT_eX]

[DOI]

Marvin Zhang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

C-Mixup: Improving Generalization in Regression.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Giving Feedback on Interactive Student Programs with Meta-Exploration.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Options via Compression.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

You Only Live Once: Single-Life Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

LAPO: Latent-Variable Advantage-Weighted Policy Optimization for Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Correct-N-Contrast: a Contrastive Approach for Improving Robustness to Spurious Correlations.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

How to Leverage Unlabeled Data in Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Improving Out-of-Distribution Robustness via Selective Augmentation.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

Robust Policy Learning over Multiple Uncertainty Sets.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Machine Learning, 2022

A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning.

[BibT_eX]

[DOI]

Archit Sharma

Rehaan Ahmad

Proceedings of the International Conference on Machine Learning, 2022

Memory-Based Model Editing at Scale.

[BibT_eX]

[DOI]

Charles Lin

Antoine Bosselut

Proceedings of the International Conference on Machine Learning, 2022

Do deep networks transfer invariances across classes?

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta-Learning with Fewer Tasks through Task Interpolation.

[BibT_eX]

[DOI]

Linjun Zhang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Autonomous Reinforcement Learning: Formalism and Benchmarking.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Extending the WILDS Benchmark for Unsupervised Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Fast Model Editing at Scale.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Vision-Based Manipulators Need to Also See from Their Hands.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

CoMPS: Continual Meta Policy Search.

[BibT_eX]

[DOI]

Proceedings of the Tenth International Conference on Learning Representations, 2022

Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference.

[BibT_eX]

[DOI]

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

R3M: A Universal Visual Representation for Robot Manipulation.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2022

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2022

Offline Reinforcement Learning at Multiple Frequencies.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 2022

Lifelong Robotic Reinforcement Learning by Retaining Experiences.

[BibT_eX]

[DOI]

Annie Xie

Proceedings of the Conference on Lifelong Learning Agents, 2022

2021

Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2021

Batch Exploration With Examples for Scalable Robotic Reinforcement Learning.

[BibT_eX]

[DOI]

IEEE Robotics Autom. Lett., 2021

How to train your robot with deep reinforcement learning: lessons we have learned.

[BibT_eX]

[DOI]

Int. J. Robotics Res., 2021

MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance.

[BibT_eX]

[DOI]

CoRR, 2021

On the Opportunities and Risks of Foundation Models.

[BibT_eX]

[DOI]

CoRR, 2021

ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback.

[BibT_eX]

[DOI]

CoRR, 2021

Persistent Reinforcement Learning via Subgoal Curricula.

[BibT_eX]

[DOI]

CoRR, 2021

FitVid: Overfitting in Pixel-Level Video Prediction.

[BibT_eX]

[DOI]

Mohammad Babaeizadeh

Mohammad Taghi Saffar

CoRR, 2021

MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale.

[BibT_eX]

[DOI]

CoRR, 2021

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills.

[BibT_eX]

[DOI]

CoRR, 2021

Discriminator Augmented Model-Based Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2021

How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned.

[BibT_eX]

[DOI]

CoRR, 2021

Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos.

[BibT_eX]

[DOI]

Annie S. Chen

Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Adaptive Risk Minimization: Learning to Adapt to Domain Shift.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Differentiable Annealed Importance Sampling and the Perils of Gradient Noise.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

COMBO: Conservative Offline Model-Based Policy Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Conservative Data Sharing for Multi-Task Offline Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Meta-learning with an Adaptive Task Scheduler.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Autonomous Reinforcement Learning via Subgoal Curricula.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Information is Power: Intrinsic Control via Information Capture.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Visual Adversarial Imitation Learning using Variational Models.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Efficiently Identifying Task Groupings for Multi-Task Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Noether Networks: meta-learning useful conserved quantities.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Offline Reinforcement Learning from Images with Latent Space Models.

[BibT_eX]

[DOI]

Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms.

[BibT_eX]

[DOI]

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Deep Reinforcement Learning amidst Continual Structured Non-Stationarity.

[BibT_eX]

[DOI]

Annie Xie

James Harrison

Proceedings of the 38th International Conference on Machine Learning, 2021

Offline Meta-Reinforcement Learning with Advantage Weighting.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Just Train Twice: Improving Group Robustness without Training Group Information.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

WILDS: A Benchmark of in-the-Wild Distribution Shifts.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Catformer: Designing Stable Transformers via Sensitivity Analysis.

[BibT_eX]

[DOI]

Jared Quincy Davis

Albert Gu

Krzysztof Choromanski

Proceedings of the 38th International Conference on Machine Learning, 2021

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

Meta-learning Symmetries by Reparameterization.

[BibT_eX]

[DOI]

Allan Zhou

Tom Knowles

Proceedings of the 9th International Conference on Learning Representations, 2021

Model-Based Visual Planning with Self-Supervised Functional Distances.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments.

[BibT_eX]

[DOI]

Proceedings of the 9th International Conference on Learning Representations, 2021

Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction.

[BibT_eX]

[DOI]

Bohan Wu

Roberto Martín-Martín

Li Fei-Fei

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Learning Language-Conditioned Robot Behavior from Offline Data and Crowd-Sourced Annotation.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

A Workflow for Offline Model-Free Robotic Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Scaling Up Multi-Task Robotic Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning.

[BibT_eX]

[DOI]

Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Challenges of Acquiring Compositional Inductive Biases via Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021

2020

Variable-Shot Adaptation for Online Meta-Learning.

[BibT_eX]

[DOI]

CoRR, 2020

WILDS: A Benchmark of in-the-Wild Distribution Shifts.

[BibT_eX]

[DOI]

Richard Lanas Phillips

CoRR, 2020

Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning.

[BibT_eX]

[DOI]

Mohammad Babaeizadeh

Mohammad Taghi Saffar

CoRR, 2020

Measuring and Harnessing Transference in Multi-Task Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Learning to be Safe: Deep RL with a Safety Critic.

[BibT_eX]

[DOI]

CoRR, 2020

MELD: Meta-Reinforcement Learning from Images via Latent State Models.

[BibT_eX]

[DOI]

CoRR, 2020

Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2020

Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift.

[BibT_eX]

[DOI]

CoRR, 2020

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors.

[BibT_eX]

[DOI]

CoRR, 2020

Deep Reinforcement Learning amidst Lifelong Non-Stationarity.

[BibT_eX]

[DOI]

Annie Xie

James Harrison

CoRR, 2020

Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling.

[BibT_eX]

[DOI]

CoRR, 2020

Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation.

[BibT_eX]

[DOI]

CoRR, 2020

MOPO: Model-based Offline Policy Optimization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Gradient Surgery for Multi-Task Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Continual Learning of Control Primitives : Skill Discovery via Reset-Games.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Weakly-Supervised Reinforcement Learning for Controllable Behavior.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Continuous Meta-Learning without Tasks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Rapidly Adaptable Legged Robots via Evolutionary Meta-Learning.

[BibT_eX]

[DOI]

Xingyou Song

Yuxiang Yang

Krzysztof Choromanski

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Scalable Multi-Task Imitation Learning with Autonomous Improvement.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

OmniTact: A Multi-Directional High-Resolution Touch Sensor.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

TRASS: Time Reversal as Self-Supervision.

[BibT_eX]

[DOI]

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Goal-Aware Prediction: Learning to Model What Matters.

[BibT_eX]

[DOI]

Silvio Savarese

Proceedings of the 37th International Conference on Machine Learning, 2020

On the Expressivity of Neural Networks for Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 37th International Conference on Machine Learning, 2020

Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Meta-Learning without Memorization.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Model Based Reinforcement Learning for Atari.

[BibT_eX]

[DOI]

Proceedings of the 8th International Conference on Learning Representations, 2020

Learning Predictive Models from Observation and Interaction.

[BibT_eX]

[DOI]

Proceedings of the Computer Vision - ECCV 2020, 2020

MELD: Meta-Reinforcement Learning from Images via Latent State Models.

[BibT_eX]

[DOI]

Proceedings of the 4th Conference on Robot Learning, 2020

Learning Latent Representations to Influence Multi-Agent Interaction.

[BibT_eX]

[DOI]

Proceedings of the 4th Conference on Robot Learning, 2020

Reinforcement Learning with Videos: Combining Offline Observations with Interaction.

[BibT_eX]

[DOI]

Proceedings of the 4th Conference on Robot Learning, 2020

Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 4th Conference on Robot Learning, 2020

Learning to Interactively Learn and Assist.

[BibT_eX]

[DOI]

Mark Woodward

Karol Hausman

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

SMiRL: Surprise Minimizing RL in Dynamic Environments.

[BibT_eX]

[DOI]

CoRR, 2019

Training an Interactive Helper.

[BibT_eX]

[DOI]

Mark Woodward

Karol Hausman

CoRR, 2019

Watch, Try, Learn: Meta-Learning from Demonstrations and Reward.

[BibT_eX]

[DOI]

CoRR, 2019

End-to-End Robotic Reinforcement Learning without Reward Engineering.

[BibT_eX]

[DOI]

CoRR, 2019

VideoFlow: A Flow-Based Generative Model for Video.

[BibT_eX]

[DOI]

CoRR, 2019

Model-Based Reinforcement Learning for Atari.

[BibT_eX]

[DOI]

CoRR, 2019

Unsupervised Visuomotor Control through Distributional Planning Networks.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XV, 2019

Improvisation through Physical Understanding: Using Novel Objects As Tools with Visual Foresight.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XV, 2019

End-To-End Robotic Reinforcement Learning without Reward Engineering.

[BibT_eX]

[DOI]

Proceedings of the Robotics: Science and Systems XV, 2019

Meta-Inverse Reinforcement Learning with Probabilistic Context Variables.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Meta-Learning with Implicit Gradients.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Guided Meta-Policy Search.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Language as an Abstraction for Hierarchical Deep Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Unsupervised Curricula for Visual Meta-Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

One-Shot Composition of Vision-Based Skills from Demonstration.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Manipulation by Feel: Touch-Based Control with Deep Predictive Models.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Robotics and Automation, 2019

Learning a Prior over Intent via Meta-Inverse Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Online Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the 36th International Conference on Machine Learning, 2019

Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL.

[BibT_eX]

[DOI]

Anusha Nagabandi

Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Reasoning About Physical Interactions with Object-Oriented Prediction and Planning.

[BibT_eX]

[DOI]

Proceedings of the 7th International Conference on Learning Representations, 2019

Unsupervised Learning via Meta-Learning.

[BibT_eX]

[DOI]

Kyle Hsu

Proceedings of the 7th International Conference on Learning Representations, 2019

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Entity Abstraction in Visual Model-Based Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

RoboNet: Large-Scale Multi-Robot Learning.

[BibT_eX]

[DOI]

Proceedings of the 3rd Annual Conference on Robot Learning, 2019

NoRML: No-Reward Meta Learning.

[BibT_eX]

[DOI]

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

Learning to Learn with Gradients.

[BibT_eX]

[DOI]

PhD thesis, 2018

Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control.

[BibT_eX]

[DOI]

CoRR, 2018

One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks.

[BibT_eX]

[DOI]

CoRR, 2018

Time Reversal as Self-Supervision.

[BibT_eX]

[DOI]

CoRR, 2018

Unsupervised Meta-Learning for Reinforcement Learning.

[BibT_eX]

[DOI]

CoRR, 2018

Stochastic Adversarial Video Prediction.

[BibT_eX]

[DOI]

CoRR, 2018

Universal Planning Networks.

[BibT_eX]

[DOI]

CoRR, 2018

Learning to Adapt: Meta-Learning for Model-Based Control.

[BibT_eX]

[DOI]

CoRR, 2018

Probabilistic Model-Agnostic Meta-Learning.

[BibT_eX]

[DOI]

Kelvin Xu

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods.

[BibT_eX]

[DOI]

Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Recasting Gradient-Based Meta-Learning as Hierarchical Bayes.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Stochastic Variational Video Prediction.

[BibT_eX]

[DOI]

Proceedings of the 6th International Conference on Learning Representations, 2018

Few-Shot Goal Inference for Visuomotor Learning and Planning.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning.

[BibT_eX]

[DOI]

Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017

Active One-shot Learning.

[BibT_eX]

[DOI]

Mark Woodward

CoRR, 2017

Reset-free guided policy search: Efficient deep reinforcement learning with stochastic initial states.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Deep visual foresight for planning robot motion.

[BibT_eX]

[DOI]

Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks.

[BibT_eX]

[DOI]

Pieter Abbeel

Proceedings of the 34th International Conference on Machine Learning, 2017

Generalizing Skills with Semi-Supervised Reinforcement Learning.

[BibT_eX]

[DOI]

Proceedings of the 5th International Conference on Learning Representations, 2017

One-Shot Visual Imitation Learning via Meta-Learning.

[BibT_eX]

[DOI]

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

Self-Supervised Visual Planning with Temporal Skip Connections.

[BibT_eX]

[DOI]

Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016

End-to-End Training of Deep Visuomotor Policies.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2016

A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models.

[BibT_eX]

[DOI]

CoRR, 2016

Adapting Deep Visuomotor Representations with Weak Pairwise Constraints.

[BibT_eX]

[DOI]

Proceedings of the Algorithmic Foundations of Robotics XII, 2016

Unsupervised Learning for Physical Interaction through Video Prediction.

[BibT_eX]

[DOI]

Ian J. Goodfellow

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Learning deep neural network policies with continuous memory states.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Deep spatial autoencoders for visuomotor learning.

[BibT_eX]

[DOI]

Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization.

[BibT_eX]

[DOI]

Pieter Abbeel

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Sloop: A pattern retrieval engine for individual animal identification.

[BibT_eX]

[DOI]

Pattern Recognit., 2015

Policy Learning with Continuous Memory States for Partially Observed Robotic Control.

[BibT_eX]

[DOI]

CoRR, 2015

Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments.

[BibT_eX]

[DOI]

CoRR, 2015

Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders.

[BibT_eX]

[DOI]

CoRR, 2015

Learning Compact Convolutional Neural Networks with Nested Dropout.

[BibT_eX]

[DOI]

Lisa Anne Hendricks

Trevor Darrell

Proceedings of the 3rd International Conference on Learning Representations, 2015

Bridging text spotting and SLAM with junction features.

[BibT_eX]

[DOI]

Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Beyond lowest-warping cost action selection in trajectory transfer.

[BibT_eX]

[DOI]

Dylan Hadfield-Menell

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014

Relevance Feedback in Biometric Retrieval of Animal Photographs.

[BibT_eX]

[DOI]

Proceedings of the Pattern Recognition - 6th Mexican Conference, 2014

2013

Vision-Based Biometrics for Conservation.

[BibT_eX]

[DOI]

Sai Ravela

James Duyck