Emmanuel Bengio | DeepAI

AI Chat

Featured Co-authors

Yoshua Bengio
448 publications
Kyunghyun Cho
218 publications
Aaron Courville
152 publications
Doina Precup
141 publications
Joelle Pineau
116 publications
Simon Lacoste-Julien
79 publications
Hugo Larochelle
75 publications
Chen Sun
74 publications
Christopher Pal
63 publications
Nicolas Ballas
36 publications
Asja Fischer
35 publications

∙ 06/07/2023

Goal-conditioned GFlowNets for Controllable Multi-Objective Molecular Design

In recent years, in-silico molecular design has received much attention ...

0 Julien Roy, et al. ∙

∙ 05/11/2023

Towards Understanding and Improving GFlowNet Training

Generative flow networks (GFlowNets) are a family of algorithms that lea...

2 Max W. Shen, et al. ∙

∙ 10/23/2022

Multi-Objective GFlowNets

In many applications of machine learning, like drug discovery and materi...

0 Moksh Jain, et al. ∙

∙ 09/26/2022

Learning GFlowNets from partial episodes for improved convergence and stability

Generative flow networks (GFlowNets) are a family of algorithms for trai...

11 Kanika Madan, et al. ∙

∙ 01/31/2022

Trajectory Balance: Improved Credit Assignment in GFlowNets

Generative Flow Networks (GFlowNets) are a method for learning a stochas...

1 Nikolay Malkin, et al. ∙

∙ 11/17/2021

GFlowNet Foundations

Generative Flow Networks (GFlowNets) have been introduced as a method to...

40 Yoshua Bengio, et al. ∙

∙ 06/08/2021

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation

This paper is about the problem of learning a stochastic policy for gene...

11 Emmanuel Bengio, et al. ∙

∙ 06/07/2021

Correcting Momentum in Temporal Difference Learning

A common optimization tool used in deep reinforcement learning is moment...

26 Emmanuel Bengio, et al. ∙

∙ 07/06/2020

TDprop: Does Jacobi Preconditioning Help Temporal Difference Learning?

We investigate whether Jacobi preconditioning, accounting for the bootst...

0 Joshua Romoff, et al. ∙

∙ 03/13/2020

Interference and Generalization in Temporal Difference Learning

We study the link between generalization and interference in temporal-di...

7 Emmanuel Bengio, et al. ∙

∙ 07/10/2018

Fooling the classifier: Ligand antagonism and adversarial examples

Machine learning algorithms are sensitive to so-called adversarial pertu...

6 Thomas J. Rademaker, et al. ∙

∙ 02/26/2018

Disentangling the independently controllable factors of variation by interacting with the world

It has been postulated that a good representation is one that disentangl...

0 Valentin Thomas, et al. ∙

∙ 08/03/2017

Independently Controllable Factors

It has been postulated that a good representation is one that disentangl...

0 Valentin Thomas, et al. ∙

∙ 06/16/2017

A Closer Look at Memorization in Deep Networks

We examine the role of memorization in deep learning, drawing connection...

0 Devansh Arpit, et al. ∙

∙ 03/22/2017

Independently Controllable Features

Finding features that disentangle the different causes of variation in r...

0 Emmanuel Bengio, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world