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08/30/2023
RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation
For robots to be useful outside labs and specialized factories we need a...
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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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05/24/2023
Barkour: Benchmarking Animal-level Agility with Quadruped Robots
Animals have evolved various agile locomotion strategies, such as sprint...
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04/26/2023
Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning
We investigate whether Deep Reinforcement Learning (Deep RL) is able to ...
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10/22/2022
Hindering Adversarial Attacks with Implicit Neural Representations
We introduce the Lossy Implicit Network Activation Coding (LINAC) defenc...
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09/05/2022
MO2: Model-Based Offline Options
The ability to discover useful behaviours from past experience and trans...
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05/31/2022
The CLRS Algorithmic Reasoning Benchmark
Learning representations of algorithms is an emerging area of machine le...
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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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03/31/2022
Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors
We investigate the use of prior knowledge of human and animal movement t...
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12/09/2021
Learning Transferable Motor Skills with Hierarchical Latent Mixture Policies
For robots operating in the real world, it is desirable to learn reusabl...
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12/09/2021
Few-Shot Keypoint Detection as Task Adaptation via Latent Embeddings
Dense object tracking, the ability to localize specific object points wi...
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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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06/16/2021
Optical Tactile Sim-to-Real Policy Transfer via Real-to-Sim Tactile Image Translation
Simulation has recently become key for deep reinforcement learning to sa...
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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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04/02/2021
Skillful Precipitation Nowcasting using Deep Generative Models of Radar
Precipitation nowcasting, the high-resolution forecasting of precipitati...
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01/21/2021
Learning rich touch representations through cross-modal self-supervision
The sense of touch is fundamental in several manipulation tasks, but rar...
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09/30/2020
S3K: Self-Supervised Semantic Keypoints for Robotic Manipulation via Multi-View Consistency
A robot's ability to act is fundamentally constrained by what it can per...
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08/06/2020
Deep Reinforcement Learning for Tactile Robotics: Learning to Type on a Braille Keyboard
Artificial touch would seem well-suited for Reinforcement Learning (RL),...
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05/15/2020
A Distributional View on Multi-Objective Policy Optimization
Many real-world problems require trading off multiple competing objectiv...
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11/19/2019
Attention Privileged Reinforcement Learning For Domain Transfer
Applying reinforcement learning (RL) to physical systems presents notabl...
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10/31/2019
Continual Unsupervised Representation Learning
Continual learning aims to improve the ability of modern learning system...
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10/23/2019
Neural Execution of Graph Algorithms
Graph Neural Networks (GNNs) are a powerful representational tool for so...
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10/13/2019
Stabilizing Transformers for Reinforcement Learning
Owing to their ability to both effectively integrate information over lo...
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08/30/2019
Meta-Learning with Warped Gradient Descent
A versatile and effective approach to meta-learning is to infer a gradie...
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03/20/2019
Learning Gentle Object Manipulation with Curiosity-Driven Deep Reinforcement Learning
Robots must know how to be gentle when they need to interact with fragil...
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03/04/2019
The StreetLearn Environment and Dataset
Navigation is a rich and well-grounded problem domain that drives progre...
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03/01/2019
Learning To Follow Directions in Street View
Navigating and understanding the real world remains a key challenge in m...
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02/12/2019
Value constrained model-free continuous control
The naive application of Reinforcement Learning algorithms to continuous...
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12/18/2018
Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks
Real world data, especially in the domain of robotics, is notoriously co...
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12/07/2018
From pixels to percepts: Highly robust edge perception and contour following using deep learning and an optical biomimetic tactile sensor
Deep learning has the potential to have the impact on robot touch that i...
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07/16/2018
Meta-Learning with Latent Embedding Optimization
Gradient-based meta-learning techniques are both widely applicable and p...
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07/11/2018
Learning Deployable Navigation Policies at Kilometer Scale from a Single Traversal
Model-free reinforcement learning has recently been shown to be effectiv...
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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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05/16/2018
Progress & Compress: A scalable framework for continual learning
We introduce a conceptually simple and scalable framework for continual ...
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04/18/2018
The Limits and Potentials of Deep Learning for Robotics
The application of deep learning in robotics leads to very specific prob...
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03/31/2018
Learning to Navigate in Cities Without a Map
Navigating through unstructured environments is a basic capability of in...
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02/26/2018
Reinforcement and Imitation Learning for Diverse Visuomotor Skills
We propose a model-free deep reinforcement learning method that leverage...
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11/28/2017
One-Shot Reinforcement Learning for Robot Navigation with Interactive Replay
Recently, model-free reinforcement learning algorithms have been shown t...
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07/13/2017
Distral: Robust Multitask Reinforcement Learning
Most deep reinforcement learning algorithms are data inefficient in comp...
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12/02/2016
Overcoming catastrophic forgetting in neural networks
The ability to learn tasks in a sequential fashion is crucial to the dev...
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11/11/2016
