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09/12/2023
OTAS: Unsupervised Boundary Detection for Object-Centric Temporal Action Segmentation
Temporal action segmentation is typically achieved by discovering the dr...
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08/28/2023
9DTact: A Compact Vision-Based Tactile Sensor for Accurate 3D Shape Reconstruction and Generalizable 6D Force Estimation
The advancements in vision-based tactile sensors have boosted the aptitu...
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07/15/2023
Can Pre-Trained Text-to-Image Models Generate Visual Goals for Reinforcement Learning?
Pre-trained text-to-image generative models can produce diverse, semanti...
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07/03/2023
MoVie: Visual Model-Based Policy Adaptation for View Generalization
Visual Reinforcement Learning (RL) agents trained on limited views face ...
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06/29/2023
ArrayBot: Reinforcement Learning for Generalizable Distributed Manipulation through Touch
We present ArrayBot, a distributed manipulation system consisting of a 1...
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06/26/2023
CEIL: Generalized Contextual Imitation Learning
In this paper, we present ContExtual Imitation Learning (CEIL), a genera...
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06/22/2023
TACO: Temporal Latent Action-Driven Contrastive Loss for Visual Reinforcement Learning
Despite recent progress in reinforcement learning (RL) from raw pixel da...
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06/05/2023
Seizing Serendipity: Exploiting the Value of Past Success in Off-Policy Actor-Critic
Learning high-quality Q-value functions plays a key role in the success ...
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02/02/2023
Is Model Ensemble Necessary? Model-based RL via a Single Model with Lipschitz Regularized Value Function
Probabilistic dynamics model ensemble is widely used in existing model-b...
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10/24/2022
Scaling up and Stabilizing Differentiable Planning with Implicit Differentiation
Differentiable planning promises end-to-end differentiability and adapti...
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10/18/2022
Simple Emergent Action Representations from Multi-Task Policy Training
Low-level sensory and motor signals in the high-dimensional spaces (e.g....
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09/28/2022
DTact: A Vision-Based Tactile Sensor that Measures High-Resolution 3D Geometry Directly from Darkness
Vision-based tactile sensors that can measure 3D geometry of the contact...
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06/24/2022
Phasic Self-Imitative Reduction for Sparse-Reward Goal-Conditioned Reinforcement Learning
It has been a recent trend to leverage the power of supervised learning ...
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05/05/2022
RoboCraft: Learning to See, Simulate, and Shape Elasto-Plastic Objects with Graph Networks
Modeling and manipulating elasto-plastic objects are essential capabilit...
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02/21/2022
Don't Touch What Matters: Task-Aware Lipschitz Data Augmentation for Visual Reinforcement Learning
One of the key challenges in visual Reinforcement Learning (RL) is to le...
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11/22/2021
Plan Better Amid Conservatism: Offline Multi-Agent Reinforcement Learning with Actor Rectification
The idea of conservatism has led to significant progress in offline rein...
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06/03/2021
Towards Learning to Play Piano with Dexterous Hands and Touch
The virtuoso plays the piano with passion, poetry and extraordinary tech...
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05/26/2021
PyTouch: A Machine Learning Library for Touch Processing
With the increased availability of rich tactile sensors, there is an equ...
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07/03/2020
Video Prediction via Example Guidance
In video prediction tasks, one major challenge is to capture the multi-m...
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03/30/2020
Multi-Task Reinforcement Learning with Soft Modularization
Multi-task learning is a very challenging problem in reinforcement learn...
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10/17/2019
Scoring-Aggregating-Planning: Learning task-agnostic priors from interactions and sparse rewards for zero-shot generalization
Humans can learn task-agnostic priors from interactive experience and ut...
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07/12/2019
Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling
Imitation learning, followed by reinforcement learning algorithms, is a ...
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12/02/2018
Disentangling Propagation and Generation for Video Prediction
Learning to predict future video frames is a challenging task. Recent ap...
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11/08/2018
Modular Architecture for StarCraft II with Deep Reinforcement Learning
We present a novel modular architecture for StarCraft II AI. The archite...
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07/10/2018
Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees
While model-based reinforcement learning has empirically been shown to s...
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12/04/2016
End-to-end Learning of Driving Models from Large-scale Video Datasets
Robust perception-action models should be learned from training data wit...
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11/13/2015