Martin Arjovsky | DeepAI

DeepAI AI Chat

Featured Co-authors

Yoshua Bengio
448 publications
Aaron Courville
152 publications
Kamalika Chaudhuri
74 publications
Charles Blundell
45 publications
Alex Lamb
37 publications
David Lopez-Paz
35 publications
Ben Poole
34 publications
Leon Bottou
33 publications
Bilal Piot
26 publications
Vincent Dumoulin
24 publications
Soumith Chintala
24 publications

∙ 05/23/2022

Throwing Away Data Improves Worst-Class Error in Imbalanced Classification

Class imbalances pervade classification problems, yet their treatment di...

0 Martin Arjovsky, et al. ∙

∙ 10/27/2021

Simple data balancing achieves competitive worst-group-accuracy

We study the problem of learning classifiers that perform well across (k...

0 Badr Youbi Idrissi, et al. ∙

∙ 03/03/2021

Out of Distribution Generalization in Machine Learning

Machine learning has achieved tremendous success in a variety of domains...

0 Martin Arjovsky, et al. ∙

∙ 06/09/2020

Low Distortion Block-Resampling with Spatially Stochastic Networks

We formalize and attack the problem of generating new images from old on...

0 Sarah Jane Hong, et al. ∙

∙ 02/14/2020

Never Give Up: Learning Directed Exploration Strategies

We propose a reinforcement learning agent to solve hard exploration game...

7 Adrià Puigdomènech Badia, et al. ∙

∙ 09/29/2019

Symplectic Recurrent Neural Networks

We propose Symplectic Recurrent Neural Networks (SRNNs) as learning algo...

0 Zhengdao Chen, et al. ∙

∙ 07/05/2019

Invariant Risk Minimization

We introduce Invariant Risk Minimization (IRM), a learning paradigm to e...

1 Martin Arjovsky, et al. ∙

∙ 12/21/2017

Geometrical Insights for Implicit Generative Modeling

Learning algorithms for implicit generative models can optimize a variet...

0 Leon Bottou, et al. ∙

∙ 03/31/2017

Improved Training of Wasserstein GANs

Generative Adversarial Networks (GANs) are powerful generative models, b...

0 Ishaan Gulrajani, et al. ∙

∙ 01/26/2017

Wasserstein GAN

We introduce a new algorithm named WGAN, an alternative to traditional G...

0 Martin Arjovsky, et al. ∙

∙ 01/17/2017

Towards Principled Methods for Training Generative Adversarial Networks

The goal of this paper is not to introduce a single algorithm or method,...

0 Martin Arjovsky, et al. ∙

∙ 06/02/2016

Adversarially Learned Inference

We introduce the adversarially learned inference (ALI) model, which join...

0 Vincent Dumoulin, et al. ∙

∙ 11/20/2015

Unitary Evolution Recurrent Neural Networks

Recurrent neural networks (RNNs) are notoriously difficult to train. Whe...

0 Martin Arjovsky, et al. ∙

∙ 05/30/2015

Saddle-free Hessian-free Optimization

Nonconvex optimization problems such as the ones in training deep neural...

0 Martin Arjovsky, et al. ∙

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