Corentin Tallec | DeepAI

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∙ 11/18/2022

Curiosity in hindsight

Consider the exploration in sparse-reward or reward-free environments, s...

0 Daniel Jarrett, et al. ∙

∙ 11/08/2022

Self-conditioned Embedding Diffusion for Text Generation

Can continuous diffusion models bring the same performance breakthrough ...

1 Robin Strudel, et al. ∙

∙ 09/30/2022

Emergent Communication: Generalization and Overfitting in Lewis Games

Lewis signaling games are a class of simple communication games for simu...

0 Mathieu Rita, et al. ∙

∙ 06/16/2022

BYOL-Explore: Exploration by Bootstrapped Prediction

We present BYOL-Explore, a conceptually simple yet general approach for ...

0 Zhaohan Daniel Guo, 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. ∙

∙ 03/30/2021

Broaden Your Views for Self-Supervised Video Learning

Most successful self-supervised learning methods are trained to align th...

3 Adria Recasens, et al. ∙

∙ 02/12/2021

Bootstrapped Representation Learning on Graphs

Current state-of-the-art self-supervised learning methods for graph neur...

0 Shantanu Thakoor, et al. ∙

∙ 01/18/2021

Learning Successor States and Goal-Dependent Values: A Mathematical Viewpoint

In reinforcement learning, temporal difference-based algorithms can be s...

0 Léonard Blier, et al. ∙

∙ 10/20/2020

BYOL works even without batch statistics

Bootstrap Your Own Latent (BYOL) is a self-supervised learning approach ...

0 Pierre H. Richemond, et al. ∙

∙ 06/13/2020

Bootstrap Your Own Latent: A New Approach to Self-Supervised Learning

We introduce Bootstrap Your Own Latent (BYOL), a new approach to self-su...

0 Jean-Bastien Grill, et al. ∙

∙ 01/28/2019

Making Deep Q-learning methods robust to time discretization

Despite remarkable successes, Deep Reinforcement Learning (DRL) is not r...

14 Corentin Tallec, et al. ∙

∙ 06/19/2018

Mixed batches and symmetric discriminators for GAN training

Generative adversarial networks (GANs) are pow- erful generative models ...

0 Thomas Lucas, et al. ∙

∙ 03/23/2018

Can recurrent neural networks warp time?

Successful recurrent models such as long short-term memories (LSTMs) and...

0 Corentin Tallec, et al. ∙

∙ 05/23/2017

Unbiasing Truncated Backpropagation Through Time

Truncated Backpropagation Through Time (truncated BPTT) is a widespread ...

0 Corentin Tallec, et al. ∙

∙ 02/16/2017

Unbiased Online Recurrent Optimization

The novel Unbiased Online Recurrent Optimization (UORO) algorithm allows...

0 Corentin Tallec, et al. ∙

∙ 07/28/2015

Training recurrent networks online without backtracking

We introduce the "NoBackTrack" algorithm to train the parameters of dyna...

0 Yann Ollivier, et al. ∙

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