Dushyant Rao | DeepAI

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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 ...

0 Konstantinos Bousmalis, et al. ∙

∙ 04/25/2023

Towards Compute-Optimal Transfer Learning

The field of transfer learning is undergoing a significant shift with th...

0 Massimo Caccia, et al. ∙

∙ 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...

0 Jingwei Zhang, et al. ∙

∙ 11/24/2022

SkillS: Adaptive Skill Sequencing for Efficient Temporally-Extended Exploration

The ability to effectively reuse prior knowledge is a key requirement wh...

0 Giulia Vezzani, et al. ∙

∙ 09/05/2022

MO2: Model-Based Offline Options

The ability to discover useful behaviours from past experience and trans...

0 Sasha Salter, et al. ∙

∙ 04/12/2022

Offline Distillation for Robot Lifelong Learning with Imbalanced Experience

Robots will experience non-stationary environment dynamics throughout th...

0 Wenxuan Zhou, et al. ∙

∙ 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...

0 Dushyant Rao, et al. ∙

∙ 06/24/2021

Task-agnostic Continual Learning with Hybrid Probabilistic Models

Learning new tasks continuously without forgetting on a constantly chang...

0 Polina Kirichenko, et al. ∙

∙ 07/30/2020

Data-efficient Hindsight Off-policy Option Learning

Solutions to most complex tasks can be decomposed into simpler, intermed...

38 Markus Wulfmeier, et al. ∙

∙ 11/19/2019

Attention Privileged Reinforcement Learning For Domain Transfer

Applying reinforcement learning (RL) to physical systems presents notabl...

16 Sasha Salter, et al. ∙

∙ 10/31/2019

Continual Unsupervised Representation Learning

Continual learning aims to improve the ability of modern learning system...

52 Dushyant Rao, et al. ∙

∙ 07/16/2018

Meta-Learning with Latent Embedding Optimization

Gradient-based meta-learning techniques are both widely applicable and p...

0 Andrei A. Rusu, et al. ∙

∙ 12/13/2016

Incorporating Human Domain Knowledge into Large Scale Cost Function Learning

Recent advances have shown the capability of Fully Convolutional Neural ...

0 Markus Wulfmeier, et al. ∙

∙ 09/29/2016

Deep Tracking on the Move: Learning to Track the World from a Moving Vehicle using Recurrent Neural Networks

This paper presents an end-to-end approach for tracking static and dynam...

0 Julie Dequaire, et al. ∙

∙ 09/21/2016

Vote3Deep: Fast Object Detection in 3D Point Clouds Using Efficient Convolutional Neural Networks

This paper proposes a computationally efficient approach to detecting ob...

0 Martin Engelcke, et al. ∙

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