Emilio Parisotto | 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. ∙

∙ 05/18/2023

A Generalist Dynamics Model for Control

We investigate the use of transformer sequence models as dynamics models...

0 Ingmar Schubert, et al. ∙

∙ 03/07/2023

Structured State Space Models for In-Context Reinforcement Learning

Structured state space sequence (S4) models have recently achieved state...

0 Chris Lu, et al. ∙

∙ 10/25/2022

In-context Reinforcement Learning with Algorithm Distillation

We propose Algorithm Distillation (AD), a method for distilling reinforc...

1 Michael (Misha) Laskin, et al. ∙

∙ 05/12/2022

A Generalist Agent

Inspired by progress in large-scale language modeling, we apply a simila...

12 Scott Reed, et al. ∙

∙ 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...

0 Steven Bohez, et al. ∙

∙ 10/20/2021

Shaking the foundations: delusions in sequence models for interaction and control

The recent phenomenal success of language models has reinvigorated machi...

68 Pedro A. Ortega, et al. ∙

∙ 04/04/2021

Efficient Transformers in Reinforcement Learning using Actor-Learner Distillation

Many real-world applications such as robotics provide hard constraints o...

0 Emilio Parisotto, et al. ∙

∙ 02/20/2021

On Proximal Policy Optimization's Heavy-tailed Gradients

Modern policy gradient algorithms, notably Proximal Policy Optimization ...

0 Saurabh Garg, et al. ∙

∙ 10/13/2019

Stabilizing Transformers for Reinforcement Learning

Owing to their ability to both effectively integrate information over lo...

7 Emilio Parisotto, et al. ∙

∙ 06/12/2019

Efficient Exploration via State Marginal Matching

To solve tasks with sparse rewards, reinforcement learning algorithms mu...

0 Lisa Lee, et al. ∙

∙ 03/07/2019

Concurrent Meta Reinforcement Learning

State-of-the-art meta reinforcement learning algorithms typically assume...

14 Emilio Parisotto, et al. ∙

∙ 02/01/2019

The Hanabi Challenge: A New Frontier for AI Research

From the early days of computing, games have been important testbeds for...

54 Nolan Bard, et al. ∙

∙ 06/17/2018

Gated Path Planning Networks

Value Iteration Networks (VINs) are effective differentiable path planni...

2 Lisa Lee, et al. ∙

∙ 02/19/2018

Global Pose Estimation with an Attention-based Recurrent Network

The ability for an agent to localize itself within an environment is cru...

0 Emilio Parisotto, et al. ∙

∙ 01/24/2018

Active Neural Localization

Localization is the problem of estimating the location of an autonomous ...

0 Devendra Singh Chaplot, et al. ∙

∙ 11/06/2016

Neuro-Symbolic Program Synthesis

Recent years have seen the proposal of a number of neural architectures ...

0 Emilio Parisotto, et al. ∙

∙ 11/09/2015

Generating Images from Captions with Attention

Motivated by the recent progress in generative models, we introduce a mo...

0 Elman Mansimov, et al. ∙

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