Sergey Levine

According to our database1, Sergey Levine authored at least 334 papers between 2009 and 2019.

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Bibliography

2019
Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.
CoRR, 2019

Deep Dynamics Models for Learning Dexterous Manipulation.
CoRR, 2019

ROBEL: Robotics Benchmarks for Learning with Low-Cost Robots.
CoRR, 2019

Recurrent Independent Mechanisms.
CoRR, 2019

Why Does Hierarchy (Sometimes) Work So Well in Reinforcement Learning?
CoRR, 2019

Meta-Learning with Implicit Gradients.
CoRR, 2019

Dynamical Distance Learning for Unsupervised and Semi-Supervised Skill Discovery.
CoRR, 2019

Dynamics-Aware Unsupervised Discovery of Skills.
CoRR, 2019

Stochastic Latent Actor-Critic: Deep Reinforcement Learning with a Latent Variable Model.
CoRR, 2019

Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives.
CoRR, 2019

When to Trust Your Model: Model-Based Policy Optimization.
CoRR, 2019

Deep Reinforcement Learning for Industrial Insertion Tasks with Visual Inputs and Natural Rewards.
CoRR, 2019

Efficient Exploration via State Marginal Matching.
CoRR, 2019

Search on the Replay Buffer: Bridging Planning and Reinforcement Learning.
CoRR, 2019

Learning Powerful Policies by Using Consistent Dynamics Model.
CoRR, 2019

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

Off-Policy Evaluation via Off-Policy Classification.
CoRR, 2019

Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction.
CoRR, 2019

Extending Deep Model Predictive Control with Safety Augmented Value Estimation from Demonstrations.
CoRR, 2019

Causal Confusion in Imitation Learning.
CoRR, 2019

SQIL: Imitation Learning via Regularized Behavioral Cloning.
CoRR, 2019

Adversarial Policies: Attacking Deep Reinforcement Learning.
CoRR, 2019

MCP: Learning Composable Hierarchical Control with Multiplicative Compositional Policies.
CoRR, 2019

REPLAB: A Reproducible Low-Cost Arm Benchmark Platform for Robotic Learning.
CoRR, 2019

Data-efficient Learning of Morphology and Controller for a Microrobot.
CoRR, 2019

PRECOG: PREdiction Conditioned On Goals in Visual Multi-Agent Settings.
CoRR, 2019

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

Improvisation through Physical Understanding: Using Novel Objects as Tools with Visual Foresight.
CoRR, 2019

Guided Meta-Policy Search.
CoRR, 2019

Wasserstein Dependency Measure for Representation Learning.
CoRR, 2019

Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables.
CoRR, 2019

Manipulation by Feel: Touch-Based Control with Deep Predictive Models.
CoRR, 2019

Skew-Fit: State-Covering Self-Supervised Reinforcement Learning.
CoRR, 2019

Learning to Identify Object Instances by Touch: Tactile Recognition via Multimodal Matching.
CoRR, 2019

Learning Latent Plans from Play.
CoRR, 2019

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

Model-Based Reinforcement Learning for Atari.
CoRR, 2019

Diagnosing Bottlenecks in Deep Q-learning Algorithms.
CoRR, 2019

Online Meta-Learning.
CoRR, 2019

From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following.
CoRR, 2019

Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight.
CoRR, 2019

Artificial Intelligence for Prosthetics - challenge solutions.
CoRR, 2019

InfoBot: Transfer and Exploration via the Information Bottleneck.
CoRR, 2019

Low Level Control of a Quadrotor with Deep Model-Based Reinforcement learning.
CoRR, 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

Learning to Walk Via Deep Reinforcement Learning.
Proceedings of the Robotics: Science and Systems XV, 2019

Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost.
Proceedings of the International Conference on Robotics and Automation, 2019

REPLAB: A Reproducible Low-Cost Arm Benchmark for Robotic Learning.
Proceedings of the International Conference on Robotics and Automation, 2019

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

Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty.
Proceedings of the International Conference on Robotics and Automation, 2019

Learning to Identify Object Instances by Touch: Tactile Recognition via Multimodal Matching.
Proceedings of the International Conference on Robotics and Automation, 2019

Data-efficient Learning of Morphology and Controller for a Microrobot.
Proceedings of the International Conference on Robotics and Automation, 2019

Generalization through Simulation: Integrating Simulated and Real Data into Deep Reinforcement Learning for Vision-Based Autonomous Flight.
Proceedings of the International Conference on Robotics and Automation, 2019

Residual Reinforcement Learning for Robot Control.
Proceedings of the International Conference on Robotics and Automation, 2019

SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning.
Proceedings of the 36th International Conference on Machine Learning, 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

EMI: Exploration with Mutual Information.
Proceedings of the 36th International Conference on Machine Learning, 2019

Diagnosing Bottlenecks in Deep Q-learning Algorithms.
Proceedings of the 36th International Conference on Machine Learning, 2019

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

Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow.
Proceedings of the 7th International Conference on Learning Representations, 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

Near-Optimal Representation Learning for Hierarchical Reinforcement Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Discriminator-Actor-Critic: Addressing Sample Inefficiency and Reward Bias in Adversarial Imitation Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Time-Agnostic Prediction: Predicting Predictable Video Frames.
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

InfoBot: Transfer and Exploration via the Information Bottleneck.
Proceedings of the 7th International Conference on Learning Representations, 2019

Recall Traces: Backtracking Models for Efficient Reinforcement Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning Actionable Representations with Goal Conditioned Policies.
Proceedings of the 7th International Conference on Learning Representations, 2019

From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following.
Proceedings of the 7th International Conference on Learning Representations, 2019

Diversity is All You Need: Learning Skills without a Reward Function.
Proceedings of the 7th International Conference on Learning Representations, 2019

Guiding Policies with Language via Meta-Learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

Automatically Composing Representation Transformations as a Means for Generalization.
Proceedings of the 7th International Conference on Learning Representations, 2019

2018
SFV: reinforcement learning of physical skills from videos.
ACM Trans. Graph., 2018

DeepMimic: example-guided deep reinforcement learning of physics-based character skills.
ACM Trans. Graph., 2018

Learning Flexible and Reusable Locomotion Primitives for a Microrobot.
IEEE Robotics and Automation Letters, 2018

More Than a Feeling: Learning to Grasp and Regrasp Using Vision and Touch.
IEEE Robotics and Automation Letters, 2018

Learning hand-eye coordination for robotic grasping with deep learning and large-scale data collection.
I. J. Robotics Res., 2018

Learning to Walk via Deep Reinforcement Learning.
CoRR, 2018

Reasoning About Physical Interactions with Object-Oriented Prediction and Planning.
CoRR, 2018

Robustness to Out-of-Distribution Inputs via Task-Aware Generative Uncertainty.
CoRR, 2018

Deep Online Learning via Meta-Learning: Continual Adaptation for Model-Based RL.
CoRR, 2018

Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks.
CoRR, 2018

Soft Actor-Critic Algorithms and Applications.
CoRR, 2018

Residual Reinforcement Learning for Robot Control.
CoRR, 2018

Visual Memory for Robust Path Following.
CoRR, 2018

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

Hierarchical Policy Design for Sample-Efficient Learning of Robot Table Tennis Through Self-Play.
CoRR, 2018

Guiding Policies with Language via Meta-Learning.
CoRR, 2018

Learning Actionable Representations with Goal-Conditioned Policies.
CoRR, 2018

Grasp2Vec: Learning Object Representations from Self-Supervised Grasping.
CoRR, 2018

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

Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation.
CoRR, 2018

Deep Imitative Models for Flexible Inference, Planning, and Control.
CoRR, 2018

Dexterous Manipulation with Deep Reinforcement Learning: Efficient, General, and Low-Cost.
CoRR, 2018

SFV: Reinforcement Learning of Physical Skills from Videos.
CoRR, 2018

Robustness via Retrying: Closed-Loop Robotic Manipulation with Self-Supervised Learning.
CoRR, 2018

Unsupervised Learning via Meta-Learning.
CoRR, 2018

Near-Optimal Representation Learning for Hierarchical Reinforcement Learning.
CoRR, 2018

EMI: Exploration with Mutual Information Maximizing State and Action Embeddings.
CoRR, 2018

Time Reversal as Self-Supervision.
CoRR, 2018

Variational Discriminator Bottleneck: Improving Imitation Learning, Inverse RL, and GANs by Constraining Information Flow.
CoRR, 2018

Few-Shot Goal Inference for Visuomotor Learning and Planning.
CoRR, 2018

Addressing Sample Inefficiency and Reward Bias in Inverse Reinforcement Learning.
CoRR, 2018

SOLAR: Deep Structured Latent Representations for Model-Based Reinforcement Learning.
CoRR, 2018

Time-Agnostic Prediction: Predicting Predictable Video Frames.
CoRR, 2018

Visual Reinforcement Learning with Imagined Goals.
CoRR, 2018

Automatically Composing Representation Transformations as a Means for Generalization.
CoRR, 2018

QT-Opt: Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation.
CoRR, 2018

Learning Instance Segmentation by Interaction.
CoRR, 2018

Few-Shot Segmentation Propagation with Guided Networks.
CoRR, 2018

Unsupervised Meta-Learning for Reinforcement Learning.
CoRR, 2018

Probabilistic Model-Agnostic Meta-Learning.
CoRR, 2018

Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings.
CoRR, 2018

Learning a Prior over Intent via Meta-Inverse Reinforcement Learning.
CoRR, 2018

Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models.
CoRR, 2018

Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition.
CoRR, 2018

More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch.
CoRR, 2018

Data-Efficient Hierarchical Reinforcement Learning.
CoRR, 2018

Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior.
CoRR, 2018

Reinforcement Learning and Control as Probabilistic Inference: Tutorial and Review.
CoRR, 2018

Latent Space Policies for Hierarchical Reinforcement Learning.
CoRR, 2018

DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills.
CoRR, 2018

Stochastic Adversarial Video Prediction.
CoRR, 2018

Universal Planning Networks.
CoRR, 2018

Recall Traces: Backtracking Models for Efficient Reinforcement Learning.
CoRR, 2018

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments.
CoRR, 2018

Learning to Run challenge: Synthesizing physiologically accurate motion using deep reinforcement learning.
CoRR, 2018

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

Composable Deep Reinforcement Learning for Robotic Manipulation.
CoRR, 2018

Learning Flexible and Reusable Locomotion Primitives for a Microrobot.
CoRR, 2018

Model-Based Value Estimation for Efficient Model-Free Reinforcement Learning.
CoRR, 2018

Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods.
CoRR, 2018

The Mirage of Action-Dependent Baselines in Reinforcement Learning.
CoRR, 2018

Temporal Difference Models: Model-Free Deep RL for Model-Based Control.
CoRR, 2018

Meta-Reinforcement Learning of Structured Exploration Strategies.
CoRR, 2018

Diversity is All You Need: Learning Skills without a Reward Function.
CoRR, 2018

Reinforcement Learning from Imperfect Demonstrations.
CoRR, 2018

Shared Autonomy via Deep Reinforcement Learning.
CoRR, 2018

One-Shot Imitation from Observing Humans via Domain-Adaptive Meta-Learning.
CoRR, 2018

Recasting Gradient-Based Meta-Learning as Hierarchical Bayes.
CoRR, 2018

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.
CoRR, 2018

Shared Autonomy via Deep Reinforcement Learning.
Proceedings of the Robotics: Science and Systems XIV, 2018

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations.
Proceedings of the Robotics: Science and Systems XIV, 2018

Where Do You Think You're Going?: Inferring Beliefs about Dynamics from Behavior.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Visual Reinforcement Learning with Imagined Goals.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Data-Efficient Hierarchical Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Visual Memory for Robust Path Following.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Meta-Reinforcement Learning of Structured Exploration Strategies.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 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 in a Handful of Trials using Probabilistic Dynamics Models.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Learning with Latent Language.
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Learning Image-Conditioned Dynamics Models for Control of Underactuated Legged Millirobots.
Proceedings of the 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2018

Time-Contrastive Networks: Self-Supervised Learning from Video.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-to-End Learning from Demonstration.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 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

Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Self-Supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Composable Deep Reinforcement Learning for Robotic Manipulation.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Deep Object-Centric Representations for Generalizable Robot Learning.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping.
Proceedings of the 2018 IEEE International Conference on Robotics and Automation, 2018

The Mirage of Action-Dependent Baselines in Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

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

Regret Minimization for Partially Observable Deep Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor.
Proceedings of the 35th International Conference on Machine Learning, 2018

Latent Space Policies for Hierarchical Reinforcement Learning.
Proceedings of the 35th International Conference on Machine Learning, 2018

Self-Consistent Trajectory Autoencoder: Hierarchical Reinforcement Learning with Trajectory Embeddings.
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

Conditional Networks for Few-Shot Semantic Segmentation.
Proceedings of the 6th International Conference on Learning Representations, 2018

Temporal Difference Models: Model-Free Deep RL for Model-Based Control.
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

Divide-and-Conquer Reinforcement Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

Reinforcement Learning from Imperfect Demonstrations.
Proceedings of the 6th International Conference on Learning Representations, 2018

Learning Robust Rewards with Adverserial Inverse Reinforcement Learning.
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

Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning.
Proceedings of the 6th International Conference on Learning Representations, 2018

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

Sim2Real Viewpoint Invariant Visual Servoing by Recurrent Control.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition, 2018

Learning Instance Segmentation by Interaction.
Proceedings of the 2018 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2018

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

Scalable Deep Reinforcement Learning for Vision-Based Robotic Manipulation.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Composable Action-Conditioned Predictors: Flexible Off-Policy Learning for Robot Navigation.
Proceedings of the 2nd Annual Conference on Robot Learning, 2018

Grasp2Vec: Learning Object Representations from Self-Supervised Grasping.
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
Unifying Map and Landmark Based Representations for Visual Navigation.
CoRR, 2017

Sim2Real View Invariant Visual Servoing by Recurrent Control.
CoRR, 2017

Divide-and-Conquer Reinforcement Learning.
CoRR, 2017

Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning.
CoRR, 2017

Neural Network Dynamics Models for Control of Under-actuated Legged Millirobots.
CoRR, 2017

Learning with Latent Language.
CoRR, 2017

Meta-Learning and Universality: Deep Representations and Gradient Descent can Approximate any Learning Algorithm.
CoRR, 2017

Regret Minimization for Partially Observable Deep Reinforcement Learning.
CoRR, 2017

Stochastic Variational Video Prediction.
CoRR, 2017

Learning Robust Rewards with Adversarial Inverse Reinforcement Learning.
CoRR, 2017

The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?
CoRR, 2017

Self-Supervised Visual Planning with Temporal Skip Connections.
CoRR, 2017

Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation.
CoRR, 2017

Learning Complex Dexterous Manipulation with Deep Reinforcement Learning and Demonstrations.
CoRR, 2017

Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping.
CoRR, 2017

One-Shot Visual Imitation Learning via Meta-Learning.
CoRR, 2017

MBMF: Model-Based Priors for Model-Free Reinforcement Learning.
CoRR, 2017

Learning Robotic Manipulation of Granular Media.
CoRR, 2017

Deep Object-Centric Representations for Generalizable Robot Learning.
CoRR, 2017

Neural Network Dynamics for Model-Based Deep Reinforcement Learning with Model-Free Fine-Tuning.
CoRR, 2017

GPLAC: Generalizing Vision-Based Robotic Skills using Weakly Labeled Images.
CoRR, 2017

Time-Contrastive Networks: Self-Supervised Learning from Multi-View Observation.
CoRR, 2017

Vision-Based Multi-Task Manipulation for Inexpensive Robots Using End-To-End Learning from Demonstration.
CoRR, 2017

Combining Self-Supervised Learning and Imitation for Vision-Based Rope Manipulation.
CoRR, 2017

Imitation from Observation: Learning to Imitate Behaviors from Raw Video via Context Translation.
CoRR, 2017

Learning Visual Servoing with Deep Features and Fitted Q-Iteration.
CoRR, 2017

Uncertainty-Aware Reinforcement Learning for Collision Avoidance.
CoRR, 2017

End-to-End Learning of Semantic Grasping.
CoRR, 2017

Reinforcement Learning with Deep Energy-Based Policies.
CoRR, 2017

Cognitive Mapping and Planning for Visual Navigation.
CoRR, 2017

Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning.
CoRR, 2017

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning.
CoRR, 2017

EX2: Exploration with Exemplar Models for Deep Reinforcement Learning.
CoRR, 2017

Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks.
CoRR, 2017

Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning.
CoRR, 2017

Goal-Driven Dynamics Learning via Bayesian Optimization.
CoRR, 2017

CAD2RL: Real Single-Image Flight Without a Single Real Image.
Proceedings of the Robotics: Science and Systems XIII, 2017

Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

EX2: Exploration with Exemplar Models for Deep Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Collective robot reinforcement learning with distributed asynchronous guided policy search.
Proceedings of the 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017

Value Iteration Networks.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Deep reinforcement learning for tensegrity robot locomotion.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Learning from the hindsight plan - Episodic MPC improvement.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Combining self-supervised learning and imitation for vision-based rope manipulation.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 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

PLATO: Policy learning using adaptive trajectory optimization.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Deep reinforcement learning for robotic manipulation with asynchronous off-policy updates.
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

Learning modular neural network policies for multi-task and multi-robot transfer.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Path integral guided policy search.
Proceedings of the 2017 IEEE International Conference on Robotics and Automation, 2017

Reinforcement Learning with Deep Energy-Based Policies.
Proceedings of the 34th International Conference on Machine Learning, 2017

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

Combining Model-Based and Model-Free Updates for Trajectory-Centric Reinforcement Learning.
Proceedings of the 34th International Conference on Machine Learning, 2017

Modular Multitask Reinforcement Learning with Policy Sketches.
Proceedings of the 34th International Conference on Machine Learning, 2017

Unsupervised Perceptual Rewards for Imitation Learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

EPOpt: Learning Robust Neural Network Policies Using Model Ensembles.
Proceedings of the 5th International Conference on Learning Representations, 2017

Learning Visual Servoing with Deep Features and Fitted Q-Iteration.
Proceedings of the 5th International Conference on Learning Representations, 2017

Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic.
Proceedings of the 5th International Conference on Learning Representations, 2017

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

Learning Invariant Feature Spaces to Transfer Skills with Reinforcement Learning.
Proceedings of the 5th International Conference on Learning Representations, 2017

GPLAC: Generalizing Vision-Based Robotic Skills Using Weakly Labeled Images.
Proceedings of the IEEE International Conference on Computer Vision, 2017

Time-Contrastive Networks: Self-Supervised Learning from Multi-view Observation.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2017

Cognitive Mapping and Planning for Visual Navigation.
Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

Learning Robotic Manipulation of Granular Media.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

End-to-End Learning of Semantic Grasping.
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 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

The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?
Proceedings of the 1st Annual Conference on Robot Learning, CoRL 2017, Mountain View, 2017

Goal-driven dynamics learning via Bayesian optimization.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

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

Collective Robot Reinforcement Learning with Distributed Asynchronous Guided Policy Search.
CoRR, 2016

Learning from the Hindsight Plan - Episodic MPC Improvement.
CoRR, 2016

Value Iteration Networks.
CoRR, 2016

Unsupervised Perceptual Rewards for Imitation Learning.
CoRR, 2016

High-Dimensional Continuous Control Using Generalized Advantage Estimation.
Proceedings of the 4th International Conference on Learning Representations, 2016

(CAD)$^2$RL: Real Single-Image Flight without a Single Real Image.
CoRR, 2016

EPOpt: Learning Robust Neural Network Policies Using Model Ensembles.
CoRR, 2016

Guided Policy Search as Approximate Mirror Descent.
CoRR, 2016

Reset-Free Guided Policy Search: Efficient Deep Reinforcement Learning with Stochastic Initial States.
CoRR, 2016

Learning Hand-Eye Coordination for Robotic Grasping with Deep Learning and Large-Scale Data Collection.
CoRR, 2016

Learning Dexterous Manipulation Policies from Experience and Imitation.
CoRR, 2016

PLATO: Policy Learning using Adaptive Trajectory Optimization.
CoRR, 2016

Backprop KF: Learning Discriminative Deterministic State Estimators.
CoRR, 2016

Learning Dexterous Manipulation for a Soft Robotic Hand from Human Demonstration.
CoRR, 2016

MuProp: Unbiased Backpropagation for Stochastic Neural Networks.
Proceedings of the 4th International Conference on Learning Representations, 2016

Continuous Deep Q-Learning with Model-based Acceleration.
CoRR, 2016

Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic.
CoRR, 2016

Deep Reinforcement Learning for Robotic Manipulation.
CoRR, 2016

Deep Reinforcement Learning for Tensegrity Robot Locomotion.
CoRR, 2016

Learning Visual Predictive Models of Physics for Playing Billiards.
Proceedings of the 4th International Conference on Learning Representations, 2016

Generalizing Skills with Semi-Supervised Reinforcement Learning.
CoRR, 2016

Guided Cost Learning: Deep Inverse Optimal Control via Policy Optimization.
CoRR, 2016

Deep Visual Foresight for Planning Robot Motion.
CoRR, 2016

Unsupervised Learning for Physical Interaction through Video Prediction.
CoRR, 2016

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

Learning Modular Neural Network Policies for Multi-Task and Multi-Robot Transfer.
CoRR, 2016

Path Integral Guided Policy Search.
CoRR, 2016

Modular Multitask Reinforcement Learning with Policy Sketches.
CoRR, 2016

Learning to Poke by Poking: Experiential Learning of Intuitive Physics.
CoRR, 2016

Guided Policy Search via Approximate Mirror Descent.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Backprop KF: Learning Discriminative Deterministic State Estimators.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 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 Hand-Eye Coordination for Robotic Grasping with Large-Scale Data Collection.
Proceedings of the International Symposium on Experimental Robotics, 2016

Learning dexterous manipulation for a soft robotic hand from human demonstrations.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

One-shot learning of manipulation skills with online dynamics adaptation and neural network priors.
Proceedings of the 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016

Learning deep neural network policies with continuous memory states.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Learning deep control policies for autonomous aerial vehicles with MPC-guided policy search.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Model-based reinforcement learning with parametrized physical models and optimism-driven exploration.
Proceedings of the 2016 IEEE International Conference on Robotics and Automation, 2016

Optimal control with learned local models: Application to dexterous manipulation.
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

Continuous Deep Q-Learning with Model-based Acceleration.
Proceedings of the 33nd International Conference on Machine Learning, 2016

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

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

Learning Deep Control Policies for Autonomous Aerial Vehicles with MPC-Guided Policy Search.
CoRR, 2015

Model-based Reinforcement Learning with Parametrized Physical Models and Optimism-Driven Exploration.
CoRR, 2015

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

Incentivizing Exploration In Reinforcement Learning With Deep Predictive Models.
CoRR, 2015

Trust Region Policy Optimization.
CoRR, 2015

Learning Contact-Rich Manipulation Skills with Guided Policy Search.
CoRR, 2015

End-to-End Training of Deep Visuomotor Policies.
CoRR, 2015

One-Shot Learning of Manipulation Skills with Online Dynamics Adaptation and Neural Network Priors.
CoRR, 2015

Recurrent Network Models for Kinematic Tracking.
CoRR, 2015

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

Learning from multiple demonstrations using trajectory-aware non-rigid registration with applications to deformable object manipulation.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Learning compound multi-step controllers under unknown dynamics.
Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Optimism-driven exploration for nonlinear systems.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Learning contact-rich manipulation skills with guided policy search.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Learning force-based manipulation of deformable objects from multiple demonstrations.
Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Trust Region Policy Optimization.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Recurrent Network Models for Human Dynamics.
Proceedings of the 2015 IEEE International Conference on Computer Vision, 2015

2014
Learning Neural Network Policies with Guided Policy Search under Unknown Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Learning Complex Neural Network Policies with Trajectory Optimization.
Proceedings of the 31th International Conference on Machine Learning, 2014

Offline policy evaluation across representations with applications to educational games.
Proceedings of the International conference on Autonomous Agents and Multi-Agent Systems, 2014

2013
Exploring Deep and Recurrent Architectures for Optimal Control.
CoRR, 2013

Variational Policy Search via Trajectory Optimization.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Guided Policy Search.
Proceedings of the 30th International Conference on Machine Learning, 2013

2012
Continuous character control with low-dimensional embeddings.
ACM Trans. Graph., 2012

Continuous Inverse Optimal Control with Locally Optimal Examples
CoRR, 2012

Physically Plausible Simulation for Character Animation.
Proceedings of the 2012 Eurographics/ACM SIGGRAPH Symposium on Computer Animation, 2012

Continuous Inverse Optimal Control with Locally Optimal Examples.
Proceedings of the 29th International Conference on Machine Learning, 2012

2011
Space-time planning with parameterized locomotion controllers.
ACM Trans. Graph., 2011

Nonlinear Inverse Reinforcement Learning with Gaussian Processes.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010
Gesture controllers.
ACM Trans. Graph., 2010

Feature Construction for Inverse Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
Real-time prosody-driven synthesis of body language.
ACM Trans. Graph., 2009


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