Martín Arjovsky

According to our database, Martín Arjovsky authored at least 19 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Why does Throwing Away Data Improve Worst-Group Error?

Kamalika Chaudhuri, Kartik Ahuja, Martín Arjovsky, David Lopez-Paz

Proceedings of the International Conference on Machine Learning, 2023

2022

Throwing Away Data Improves Worst-Class Error in Imbalanced Classification.

Martín Arjovsky, Kamalika Chaudhuri, David Lopez-Paz

CoRR, 2022

Simple data balancing achieves competitive worst-group-accuracy.

Badr Youbi Idrissi, Martín Arjovsky, Mohammad Pezeshki, David Lopez-Paz

Proceedings of the 1st Conference on Causal Learning and Reasoning, 2022

2021

Out of Distribution Generalization in Machine Learning.

Martín Arjovsky

CoRR, 2021

Linear unit-tests for invariance discovery.

Benjamin Aubin, Agnieszka Slowik, Martín Arjovsky, Léon Bottou, David Lopez-Paz

CoRR, 2021

2020

Out of Distribution Generalization in Machine Learning.

Martín Arjovsky

PhD thesis, 2020

Low Distortion Block-Resampling with Spatially Stochastic Networks.

Sarah Jane Hong, Martín Arjovsky, Darryl Barnhart, Ian Thompson

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Symplectic Recurrent Neural Networks.

Zhengdao Chen, Jianyu Zhang, Martín Arjovsky, Léon Bottou

Proceedings of the 8th International Conference on Learning Representations, 2020

Never Give Up: Learning Directed Exploration Strategies.

Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andrew Bolt, Charles Blundell

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Invariant Risk Minimization.

Martín Arjovsky, Léon Bottou, Ishaan Gulrajani, David Lopez-Paz

CoRR, 2019

2017

Wasserstein GAN.

Martín Arjovsky, Soumith Chintala, Léon Bottou

CoRR, 2017

Improved Training of Wasserstein GANs.

Ishaan Gulrajani, Faruk Ahmed, Martín Arjovsky, Vincent Dumoulin, Aaron C. Courville

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Wasserstein Generative Adversarial Networks.

Martín Arjovsky, Soumith Chintala, Léon Bottou

Proceedings of the 34th International Conference on Machine Learning, 2017

Adversarially Learned Inference.

Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville

Proceedings of the 5th International Conference on Learning Representations, 2017

Towards Principled Methods for Training Generative Adversarial Networks.

Martín Arjovsky, Léon Bottou

Proceedings of the 5th International Conference on Learning Representations, 2017

Geometrical Insights for Implicit Generative Modeling.

Léon Bottou, Martín Arjovsky, David Lopez-Paz, Maxime Oquab

Proceedings of the Braverman Readings in Machine Learning. Key Ideas from Inception to Current State, 2017

2016

Optimizing Transcoder Quality Targets Using a Neural Network with an Embedded Bitrate Model.

Michele Covell, Martín Arjovsky, Yao-Chung Lin, Anil C. Kokaram

Proceedings of the Visual Information Processing and Communication VII, 2016

Unitary Evolution Recurrent Neural Networks.

Martín Arjovsky, Amar Shah, Yoshua Bengio

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Saddle-free Hessian-free optimization for Deep Learning.

Martín Arjovsky

CoRR, 2015