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06/20/2023
RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation
The ability to leverage heterogeneous robotic experience from different ...
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05/18/2023
A Generalist Dynamics Model for Control
We investigate the use of transformer sequence models as dynamics models...
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02/24/2023
Leveraging Jumpy Models for Planning and Fast Learning in Robotic Domains
In this paper we study the problem of learning multi-step dynamics predi...
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05/12/2022
A Generalist Agent
Inspired by progress in large-scale language modeling, we apply a simila...
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05/06/2022
How to Spend Your Robot Time: Bridging Kickstarting and Offline Reinforcement Learning for Vision-based Robotic Manipulation
Reinforcement learning (RL) has been shown to be effective at learning c...
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04/21/2022
Revisiting Gaussian mixture critics in off-policy reinforcement learning: a sample-based approach
Actor-critic algorithms that make use of distributional policy evaluatio...
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10/12/2021
Beyond Pick-and-Place: Tackling Robotic Stacking of Diverse Shapes
We study the problem of robotic stacking with objects of complex geometr...
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10/07/2021
Evaluating model-based planning and planner amortization for continuous control
There is a widespread intuition that model-based control methods should ...
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08/23/2021
Collect Infer – a fresh look at data-efficient Reinforcement Learning
This position paper proposes a fresh look at Reinforcement Learning (RL)...
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06/15/2021
On Multi-objective Policy Optimization as a Tool for Reinforcement Learning
Many advances that have improved the robustness and efficiency of deep r...
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01/23/2021
Rethinking Exploration for Sample-Efficient Policy Learning
Off-policy reinforcement learning for control has made great strides in ...
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10/28/2020
Training Generative Adversarial Networks by Solving Ordinary Differential Equations
The instability of Generative Adversarial Network (GAN) training has fre...
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10/16/2020
Learning Dexterous Manipulation from Suboptimal Experts
Learning dexterous manipulation in high-dimensional state-action spaces ...
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10/12/2020
Local Search for Policy Iteration in Continuous Control
We present an algorithm for local, regularized, policy improvement in re...
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06/26/2020
Critic Regularized Regression
Offline reinforcement learning (RL), also known as batch RL, offers the ...
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05/15/2020
Simple Sensor Intentions for Exploration
Modern reinforcement learning algorithms can learn solutions to increasi...
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02/19/2020
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning
Off-policy reinforcement learning algorithms promise to be applicable in...
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01/02/2020
Continuous-Discrete Reinforcement Learning for Hybrid Control in Robotics
Many real-world control problems involve both discrete decision variable...
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11/05/2019
Quinoa: a Q-function You Infer Normalized Over Actions
We present an algorithm for learning an approximate action-value soft Q-...
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10/09/2019
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models
Humans are masters at quickly learning many complex tasks, relying on an...
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09/26/2019
V-MPO: On-Policy Maximum a Posteriori Policy Optimization for Discrete and Continuous Control
Some of the most successful applications of deep reinforcement learning ...
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06/26/2019
Regularized Hierarchical Policies for Compositional Transfer in Robotics
The successful application of flexible, general learning algorithms -- s...
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06/18/2019
Robust Reinforcement Learning for Continuous Control with Model Misspecification
We provide a framework for incorporating robustness -- to perturbations ...
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01/03/2019
Self-supervised Learning of Image Embedding for Continuous Control
Operating directly from raw high dimensional sensory inputs like images ...
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12/05/2018
Relative Entropy Regularized Policy Iteration
We present an off-policy actor-critic algorithm for Reinforcement Learni...
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06/14/2018
Maximum a Posteriori Policy Optimisation
We introduce a new algorithm for reinforcement learning called Maximum a...
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06/04/2018
Graph networks as learnable physics engines for inference and control
Understanding and interacting with everyday physical scenes requires ric...
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02/28/2018
Learning by Playing - Solving Sparse Reward Tasks from Scratch
We propose Scheduled Auxiliary Control (SAC-X), a new learning paradigm ...
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03/15/2017
Deep learning with convolutional neural networks for EEG decoding and visualization
A revised version of this article is now available at Human Brain Mappin...
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12/16/2016
Deep Reinforcement Learning with Successor Features for Navigation across Similar Environments
In this paper we consider the problem of robot navigation in simple maze...
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12/02/2016
Asynchronous Stochastic Gradient MCMC with Elastic Coupling
We consider parallel asynchronous Markov Chain Monte Carlo (MCMC) sampli...
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11/19/2015
Unsupervised and Semi-supervised Learning with Categorical Generative Adversarial Networks
In this paper we present a method for learning a discriminative classifi...
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07/24/2015
Multimodal Deep Learning for Robust RGB-D Object Recognition
Robust object recognition is a crucial ingredient of many, if not all, r...
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06/24/2015
Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images
We introduce Embed to Control (E2C), a method for model learning and con...
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12/21/2014
Striving for Simplicity: The All Convolutional Net
Most modern convolutional neural networks (CNNs) used for object recogni...
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11/21/2014
Learning to Generate Chairs, Tables and Cars with Convolutional Networks
We train generative 'up-convolutional' neural networks which are able to...
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06/26/2014
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks
Deep convolutional networks have proven to be very successful in learnin...
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12/20/2013
Improving Deep Neural Networks with Probabilistic Maxout Units
We present a probabilistic variant of the recently introduced maxout uni...
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12/18/2013
