Chelsea Finn

According to our database1, Chelsea Finn authored at least 89 papers between 2013 and 2019.

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Bibliography

2019
Meta-Inverse Reinforcement Learning with Probabilistic Context Variables.
CoRR, 2019

Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal Generation.
CoRR, 2019

Meta-Learning with Implicit Gradients.
CoRR, 2019

Learning to Interactively Learn and Assist.
CoRR, 2019

Training an Interactive Helper.
CoRR, 2019

Language as an Abstraction for Hierarchical Deep Reinforcement Learning.
CoRR, 2019

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

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

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

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

NoRML: No-Reward Meta Learning.
CoRR, 2019

Model-Based Reinforcement Learning for Atari.
CoRR, 2019

Online Meta-Learning.
CoRR, 2019

Unsupervised Visuomotor Control through Distributional Planning Networks.
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

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

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

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

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

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

Unsupervised Learning via Meta-Learning.
CoRR, 2018

Time Reversal as Self-Supervision.
CoRR, 2018

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

Unsupervised Meta-Learning for Reinforcement Learning.
CoRR, 2018

Probabilistic Model-Agnostic Meta-Learning.
CoRR, 2018

Learning a Prior over Intent via Meta-Inverse 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

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

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

Stochastic Variational Video Prediction.
CoRR, 2017

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

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

Active One-shot Learning.
CoRR, 2017

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

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

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 Recognition, 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

End-to-End Training of Deep Visuomotor Policies.
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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