Chelsea Finn

Orcid: 0000-0001-6298-0874

Affiliations:
  • Stanford University, CA, USA


According to our database1, Chelsea Finn authored at least 292 papers between 2013 and 2024.

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Bibliography

2024
Bayesian Embeddings for Few-Shot Open World Recognition.
IEEE Trans. Pattern Anal. Mach. Intell., March, 2024

Conservative Prediction via Data-Driven Confidence Minimization.
Trans. Mach. Learn. Res., 2024

RoboCrowd: Scaling Robot Data Collection through Crowdsourcing.
CoRR, 2024

π<sub>0</sub>: A Vision-Language-Action Flow Model for General Robot Control.
CoRR, 2024

Grounding by Trying: LLMs with Reinforcement Learning-Enhanced Retrieval.
CoRR, 2024

ALOHA Unleashed: A Simple Recipe for Robot Dexterity.
CoRR, 2024

Generative Reward Models.
CoRR, 2024

Don't Cut Corners: Exact Conditions for Modularity in Biologically Inspired Representations.
CoRR, 2024

Helpful DoggyBot: Open-World Object Fetching using Legged Robots and Vision-Language Models.
CoRR, 2024

Bidirectional Decoding: Improving Action Chunking via Closed-Loop Resampling.
CoRR, 2024

Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents.
CoRR, 2024

PERSONA: A Reproducible Testbed for Pluralistic Alignment.
CoRR, 2024

Surgical Robot Transformer (SRT): Imitation Learning for Surgical Tasks.
CoRR, 2024

Affordance-Guided Reinforcement Learning via Visual Prompting.
CoRR, 2024

Robotic Control via Embodied Chain-of-Thought Reasoning.
CoRR, 2024

Mobility VLA: Multimodal Instruction Navigation with Long-Context VLMs and Topological Graphs.
CoRR, 2024

MJ-Bench: Is Your Multimodal Reward Model Really a Good Judge for Text-to-Image Generation?
CoRR, 2024

Commonsense Reasoning for Legged Robot Adaptation with Vision-Language Models.
CoRR, 2024

To Err is Robotic: Rapid Value-Based Trial-and-Error during Deployment.
CoRR, 2024

HumanPlus: Humanoid Shadowing and Imitation from Humans.
CoRR, 2024

OpenVLA: An Open-Source Vision-Language-Action Model.
CoRR, 2024

Scaling Laws for Reward Model Overoptimization in Direct Alignment Algorithms.
CoRR, 2024

Octo: An Open-Source Generalist Robot Policy.
CoRR, 2024

Evaluating Real-World Robot Manipulation Policies in Simulation.
CoRR, 2024

ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation.
CoRR, 2024

From <i>r</i> to Q<sup>*</sup>: Your Language Model is Secretly a Q-Function.
CoRR, 2024

Yell At Your Robot: Improving On-the-Fly from Language Corrections.
CoRR, 2024

Efficient Data Collection for Robotic Manipulation via Compositional Generalization.
CoRR, 2024

Pushing the Limits of Cross-Embodiment Learning for Manipulation and Navigation.
CoRR, 2024

A Critical Evaluation of AI Feedback for Aligning Large Language Models.
CoRR, 2024

Aligning Modalities in Vision Large Language Models via Preference Fine-tuning.
CoRR, 2024

Universal Neural Functionals.
CoRR, 2024

AutoRT: Embodied Foundation Models for Large Scale Orchestration of Robotic Agents.
CoRR, 2024

AutoFT: Robust Fine-Tuning by Optimizing Hyperparameters on OOD Data.
CoRR, 2024

Mobile ALOHA: Learning Bimanual Mobile Manipulation with Low-Cost Whole-Body Teleoperation.
CoRR, 2024

Clarify: Improving Model Robustness With Natural Language Corrections.
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.
Proceedings of the 55th ACM Technical Symposium on Computer Science Education, 2024

Policy Architectures for Compositional Generalization in Control.
RLJ, 2024

D5RL: Diverse Datasets for Data-Driven Deep Reinforcement Learning.
RLJ, 2024

Efficient imitation learning with conservative world models.
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.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation.
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.
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Proceedings of the IEEE International Conference on Robotics and Automation, 2024

SERL: A Software Suite for Sample-Efficient Robotic Reinforcement Learning.
Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Learning to Explore in POMDPs with Informational Rewards.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Preference Fine-Tuning of LLMs Should Leverage Suboptimal, On-Policy Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

RLVF: Learning from Verbal Feedback without Overgeneralization.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tripod: Three Complementary Inductive Biases for Disentangled Representation Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Improving Domain Generalization with Domain Relations.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Self-Guided Masked Autoencoders for Domain-Agnostic Self-Supervised Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Fine-Tuning Language Models for Factuality.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Language Model Detectors Are Easily Optimized Against.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

An Emulator for Fine-tuning Large Language Models using Small Language Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Project and Probe: Sample-Efficient Adaptation by Interpolating Orthogonal Features.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Calibrating Language Models with Adaptive Temperature Scaling.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

PIGEON: Predicting Image Geolocations.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Disentangling Length from Quality in Direct Preference Optimization.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
Multi-Domain Long-Tailed Learning by Augmenting Disentangled Representations.
Trans. Mach. Learn. Res., 2023

What Makes Pre-Trained Visual Representations Successful for Robust Manipulation?
CoRR, 2023

Adapt On-the-Go: Behavior Modulation for Single-Life Robot Deployment.
CoRR, 2023

Contrastive Preference Learning: Learning from Human Feedback without RL.
CoRR, 2023

Zero-Shot Robotic Manipulation with Pretrained Image-Editing Diffusion Models.
CoRR, 2023

Open X-Embodiment: Robotic Learning Datasets and RT-X Models.
CoRR, 2023

Offline Retraining for Online RL: Decoupled Policy Learning to Mitigate Exploration Bias.
CoRR, 2023

Giving Robots a Hand: Learning Generalizable Manipulation with Eye-in-Hand Human Video Demonstrations.
CoRR, 2023

Confidence-Based Model Selection: When to Take Shortcuts for Subpopulation Shifts.
CoRR, 2023

Cal-QL: Calibrated Offline RL Pre-Training for Efficient Online Fine-Tuning.
CoRR, 2023

Open-World Object Manipulation using Pre-trained Vision-Language Models.
CoRR, 2023

Permutation Equivariant Neural Functionals.
CoRR, 2023

Project and Probe: Sample-Efficient Domain Adaptation by Interpolating Orthogonal Features.
CoRR, 2023

Leveraging Domain Relations for Domain Generalization.
CoRR, 2023

A Survey of Meta-Reinforcement Learning.
CoRR, 2023

Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware.
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.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Language-Driven Representation Learning for Robotics.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023

Behavior Retrieval: Few-Shot Imitation Learning by Querying Unlabeled Datasets.
Proceedings of the Robotics: Science and Systems XIX, Daegu, 2023


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

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

Disentanglement via Latent Quantization.
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.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Contrastive Example-Based Control.
Proceedings of the Learning for Dynamics and Control Conference, 2023

Train Offline, Test Online: A Real Robot Learning Benchmark.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

DetectGPT: Zero-Shot Machine-Generated Text Detection using Probability Curvature.
Proceedings of the International Conference on Machine Learning, 2023

Simple Embodied Language Learning as a Byproduct of Meta-Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

A Control-Centric Benchmark for Video Prediction.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Diversify and Disambiguate: Out-of-Distribution Robustness via Disagreement.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Surgical Fine-Tuning Improves Adaptation to Distribution Shifts.
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.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Meta-Learning Online Adaptation of Language Models.
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.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023


Robot Parkour Learning.
Proceedings of the Conference on Robot Learning, 2023

Polybot: Training One Policy Across Robots While Embracing Variability.
Proceedings of the Conference on Robot Learning, 2023

BridgeData V2: A Dataset for Robot Learning at Scale.
Proceedings of the Conference on Robot Learning, 2023

Open-World Object Manipulation using Pre-Trained Vision-Language Models.
Proceedings of the Conference on Robot Learning, 2023

Waypoint-Based Imitation Learning for Robotic Manipulation.
Proceedings of the Conference on Robot Learning, 2023

Self-Improving Robots: End-to-End Autonomous Visuomotor Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 2023

MOTO: Offline Pre-training to Online Fine-tuning for Model-based Robot Learning.
Proceedings of the Conference on Robot Learning, 2023


Self-Destructing Models: Increasing the Costs of Harmful Dual Uses of Foundation Models.
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.
J. Mach. Learn. Res., 2022

Knowledge-Driven New Drug Recommendation.
CoRR, 2022

Pre-Training for Robots: Offline RL Enables Learning New Tasks from a Handful of Trials.
CoRR, 2022

Learning to Reason With Relational Abstractions.
CoRR, 2022

Do As I Can, Not As I Say: Grounding Language in Robotic Affordances.
CoRR, 2022

Latent-Variable Advantage-Weighted Policy Optimization for Offline RL.
CoRR, 2022

Diversify and Disambiguate: Learning From Underspecified Data.
CoRR, 2022

Fully Online Meta-Learning Without Task Boundaries.
CoRR, 2022

Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets.
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.
Proceedings of the Robotics: Science and Systems XVIII, New York City, NY, USA, June 27, 2022

MEMO: Test Time Robustness via Adaptation and Augmentation.
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.
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.
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.
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.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Options via Compression.
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.
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.
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.
Proceedings of the International Conference on Machine Learning, 2022

How to Leverage Unlabeled Data in Offline Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022

Improving Out-of-Distribution Robustness via Selective Augmentation.
Proceedings of the International Conference on Machine Learning, 2022

Robust Policy Learning over Multiple Uncertainty Sets.
Proceedings of the International Conference on Machine Learning, 2022

A State-Distribution Matching Approach to Non-Episodic Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2022

Memory-Based Model Editing at Scale.
Proceedings of the International Conference on Machine Learning, 2022

Do deep networks transfer invariances across classes?
Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta-Learning with Fewer Tasks through Task Interpolation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Autonomous Reinforcement Learning: Formalism and Benchmarking.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Extending the WILDS Benchmark for Unsupervised Adaptation.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Fast Model Editing at Scale.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Vision-Based Manipulators Need to Also See from Their Hands.
Proceedings of the Tenth International Conference on Learning Representations, 2022

CoMPS: Continual Meta Policy Search.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

R3M: A Universal Visual Representation for Robot Manipulation.
Proceedings of the Conference on Robot Learning, 2022


Offline Reinforcement Learning at Multiple Frequencies.
Proceedings of the Conference on Robot Learning, 2022

Lifelong Robotic Reinforcement Learning by Retaining Experiences.
Proceedings of the Conference on Lifelong Learning Agents, 2022

2021
Recovery RL: Safe Reinforcement Learning With Learned Recovery Zones.
IEEE Robotics Autom. Lett., 2021

Batch Exploration With Examples for Scalable Robotic Reinforcement Learning.
IEEE Robotics Autom. Lett., 2021

How to train your robot with deep reinforcement learning: lessons we have learned.
Int. J. Robotics Res., 2021

MESA: Offline Meta-RL for Safe Adaptation and Fault Tolerance.
CoRR, 2021

On the Opportunities and Risks of Foundation Models.
CoRR, 2021

ProtoTransformer: A Meta-Learning Approach to Providing Student Feedback.
CoRR, 2021

Persistent Reinforcement Learning via Subgoal Curricula.
CoRR, 2021

FitVid: Overfitting in Pixel-Level Video Prediction.
CoRR, 2021

MT-Opt: Continuous Multi-Task Robotic Reinforcement Learning at Scale.
CoRR, 2021

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills.
CoRR, 2021

Discriminator Augmented Model-Based Reinforcement Learning.
CoRR, 2021

How to Train Your Robot with Deep Reinforcement Learning; Lessons We've Learned.
CoRR, 2021

Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos.
Proceedings of the Robotics: Science and Systems XVII, Virtual Event, July 12-16, 2021., 2021

Adaptive Risk Minimization: Learning to Adapt to Domain Shift.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Proceedings of the 3rd Annual Conference on Learning for Dynamics and Control, 2021

Bayesian Meta-Learning for Few-Shot Policy Adaptation Across Robotic Platforms.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2021

Deep Reinforcement Learning amidst Continual Structured Non-Stationarity.
Proceedings of the 38th International Conference on Machine Learning, 2021

Offline Meta-Reinforcement Learning with Advantage Weighting.
Proceedings of the 38th International Conference on Machine Learning, 2021

Decoupling Exploration and Exploitation for Meta-Reinforcement Learning without Sacrifices.
Proceedings of the 38th International Conference on Machine Learning, 2021

Just Train Twice: Improving Group Robustness without Training Group Information.
Proceedings of the 38th International Conference on Machine Learning, 2021


Catformer: Designing Stable Transformers via Sensitivity Analysis.
Proceedings of the 38th International Conference on Machine Learning, 2021

Actionable Models: Unsupervised Offline Reinforcement Learning of Robotic Skills.
Proceedings of the 38th International Conference on Machine Learning, 2021

Meta-learning Symmetries by Reparameterization.
Proceedings of the 9th International Conference on Learning Representations, 2021

Model-Based Visual Planning with Self-Supervised Functional Distances.
Proceedings of the 9th International Conference on Learning Representations, 2021

SMiRL: Surprise Minimizing Reinforcement Learning in Unstable Environments.
Proceedings of the 9th International Conference on Learning Representations, 2021

Greedy Hierarchical Variational Autoencoders for Large-Scale Video Prediction.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Example-Driven Model-Based Reinforcement Learning for Solving Long-Horizon Visuomotor Tasks.
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.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

A Workflow for Offline Model-Free Robotic Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Scaling Up Multi-Task Robotic Reinforcement Learning.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

BC-Z: Zero-Shot Task Generalization with Robotic Imitation Learning.
Proceedings of the Conference on Robot Learning, 8-11 November 2021, London, UK., 2021

Challenges of Acquiring Compositional Inductive Biases via Meta-Learning.
Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021

2020
Variable-Shot Adaptation for Online Meta-Learning.
CoRR, 2020

WILDS: A Benchmark of in-the-Wild Distribution Shifts.
CoRR, 2020

Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning.
CoRR, 2020

Measuring and Harnessing Transference in Multi-Task Learning.
CoRR, 2020

Learning to be Safe: Deep RL with a Safety Critic.
CoRR, 2020

MELD: Meta-Reinforcement Learning from Images via Latent State Models.
CoRR, 2020

Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning.
CoRR, 2020

Adaptive Risk Minimization: A Meta-Learning Approach for Tackling Group Shift.
CoRR, 2020

Long-Horizon Visual Planning with Goal-Conditioned Hierarchical Predictors.
CoRR, 2020

Deep Reinforcement Learning amidst Lifelong Non-Stationarity.
CoRR, 2020

Meta-Reinforcement Learning Robust to Distributional Shift via Model Identification and Experience Relabeling.
CoRR, 2020

Efficient Adaptation for End-to-End Vision-Based Robotic Manipulation.
CoRR, 2020

MOPO: Model-based Offline Policy Optimization.
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.
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.
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.
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.
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.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Continuous Meta-Learning without Tasks.
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.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2020

Scalable Multi-Task Imitation Learning with Autonomous Improvement.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

OmniTact: A Multi-Directional High-Resolution Touch Sensor.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

TRASS: Time Reversal as Self-Supervision.
Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Cautious Adaptation For Reinforcement Learning in Safety-Critical Settings.
Proceedings of the 37th International Conference on Machine Learning, 2020

Goal-Aware Prediction: Learning to Model What Matters.
Proceedings of the 37th International Conference on Machine Learning, 2020

On the Expressivity of Neural Networks for Deep Reinforcement Learning.
Proceedings of the 37th International Conference on Machine Learning, 2020

Watch, Try, Learn: Meta-Learning from Demonstrations and Rewards.
Proceedings of the 8th International Conference on Learning Representations, 2020

Meta-Learning without Memorization.
Proceedings of the 8th International Conference on Learning Representations, 2020

Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation.
Proceedings of the 8th International Conference on Learning Representations, 2020

VideoFlow: A Conditional Flow-Based Model for Stochastic Video Generation.
Proceedings of the 8th International Conference on Learning Representations, 2020

Model Based Reinforcement Learning for Atari.
Proceedings of the 8th International Conference on Learning Representations, 2020

Learning Predictive Models from Observation and Interaction.
Proceedings of the Computer Vision - ECCV 2020, 2020

MELD: Meta-Reinforcement Learning from Images via Latent State Models.
Proceedings of the 4th Conference on Robot Learning, 2020

Learning Latent Representations to Influence Multi-Agent Interaction.
Proceedings of the 4th Conference on Robot Learning, 2020

Reinforcement Learning with Videos: Combining Offline Observations with Interaction.
Proceedings of the 4th Conference on Robot Learning, 2020

Never Stop Learning: The Effectiveness of Fine-Tuning in Robotic Reinforcement Learning.
Proceedings of the 4th Conference on Robot Learning, 2020

Learning to Interactively Learn and Assist.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
SMiRL: Surprise Minimizing RL in Dynamic Environments.
CoRR, 2019

Training an Interactive Helper.
CoRR, 2019

Watch, Try, Learn: Meta-Learning from Demonstrations and Reward.
CoRR, 2019

End-to-End Robotic Reinforcement Learning without Reward Engineering.
CoRR, 2019

VideoFlow: A Flow-Based Generative Model for Video.
CoRR, 2019

Model-Based Reinforcement Learning for Atari.
CoRR, 2019

Unsupervised Visuomotor Control through Distributional Planning Networks.
Proceedings of the Robotics: Science and Systems XV, 2019

Improvisation through Physical Understanding: Using Novel Objects As Tools with Visual Foresight.
Proceedings of the Robotics: Science and Systems XV, 2019

End-To-End Robotic Reinforcement Learning without Reward Engineering.
Proceedings of the Robotics: Science and Systems XV, 2019

Meta-Inverse Reinforcement Learning with Probabilistic Context Variables.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Meta-Learning with Implicit Gradients.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Guided Meta-Policy Search.
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.
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.
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.
Proceedings of the 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2019

Manipulation by Feel: Touch-Based Control with Deep Predictive Models.
Proceedings of the International Conference on Robotics and Automation, 2019

Learning a Prior over Intent via Meta-Inverse Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables.
Proceedings of the 36th International Conference on Machine Learning, 2019

Online Meta-Learning.
Proceedings of the 36th International Conference on Machine Learning, 2019

Deep Online Learning Via Meta-Learning: Continual Adaptation for Model-Based RL.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Adapt in Dynamic, Real-World Environments through Meta-Reinforcement Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Reasoning About Physical Interactions with Object-Oriented Prediction and Planning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Unsupervised Learning via Meta-Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Meta-World: A Benchmark and Evaluation for Multi-Task and Meta Reinforcement Learning.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

Entity Abstraction in Visual Model-Based Reinforcement Learning.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

RoboNet: Large-Scale Multi-Robot Learning.
Proceedings of the 3rd Annual Conference on Robot Learning, 2019

NoRML: No-Reward Meta Learning.
Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018
Learning to Learn with Gradients.
PhD thesis, 2018

Visual Foresight: Model-Based Deep Reinforcement Learning for Vision-Based Robotic Control.
CoRR, 2018

One-Shot Hierarchical Imitation Learning of Compound Visuomotor Tasks.
CoRR, 2018

Time Reversal as Self-Supervision.
CoRR, 2018

Unsupervised Meta-Learning for Reinforcement Learning.
CoRR, 2018

Stochastic Adversarial Video Prediction.
CoRR, 2018

Universal Planning Networks.
CoRR, 2018

Learning to Adapt: Meta-Learning for Model-Based Control.
CoRR, 2018

Probabilistic Model-Agnostic Meta-Learning.
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.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Universal Planning Networks: Learning Generalizable Representations for Visuomotor Control.
Proceedings of the 35th International Conference on Machine Learning, 2018

One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

Recasting Gradient-Based Meta-Learning as Hierarchical Bayes.
Proceedings of the 6th International Conference on Learning Representations, 2018

Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm.
Proceedings of the 6th International Conference on Learning Representations, 2018

Stochastic Variational Video Prediction.
Proceedings of the 6th International Conference on Learning Representations, 2018

Few-Shot Goal Inference for Visuomotor Learning and Planning.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

2017
Active One-shot Learning.
CoRR, 2017

Reset-free guided policy search: Efficient deep reinforcement learning with stochastic initial states.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Deep visual foresight for planning robot motion.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks.
Proceedings of the 34th International Conference on Machine Learning, 2017

Generalizing Skills with Semi-Supervised Reinforcement Learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

One-Shot Visual Imitation Learning via Meta-Learning.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

Self-Supervised Visual Planning with Temporal Skip Connections.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

2016
End-to-End Training of Deep Visuomotor Policies.
J. Mach. Learn. Res., 2016

A Connection between Generative Adversarial Networks, Inverse Reinforcement Learning, and Energy-Based Models.
CoRR, 2016

Adapting Deep Visuomotor Representations with Weak Pairwise Constraints.
Proceedings of the Algorithmic Foundations of Robotics XII, 2016

Unsupervised Learning for Physical Interaction through Video Prediction.
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.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Deep spatial autoencoders for visuomotor learning.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Sloop: A pattern retrieval engine for individual animal identification.
Pattern Recognit., 2015

Policy Learning with Continuous Memory States for Partially Observed Robotic Control.
CoRR, 2015

Towards Adapting Deep Visuomotor Representations from Simulated to Real Environments.
CoRR, 2015

Learning Visual Feature Spaces for Robotic Manipulation with Deep Spatial Autoencoders.
CoRR, 2015

Learning Compact Convolutional Neural Networks with Nested Dropout.
Proceedings of the 3rd International Conference on Learning Representations, 2015

Bridging text spotting and SLAM with junction features.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Beyond lowest-warping cost action selection in trajectory transfer.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014
Relevance Feedback in Biometric Retrieval of Animal Photographs.
Proceedings of the Pattern Recognition - 6th Mexican Conference, 2014

2013
Vision-Based Biometrics for Conservation.
Proceedings of the Pattern Recognition - 5th Mexican Conference, 2013


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