Saddle-free Hessian-free optimization for Deep Learning. - Martín Arjovsky (CoRR, 2015)

Unitary Evolution Recurrent Neural Networks. - Martín Arjovsky; Amar Shah 001; Yoshua Bengio (ICML, 2016)

Optimizing Transcoder Quality Targets Using a Neural Network with an Embedded Bitrate Model. - Michele Covell; Martín Arjovsky; Yao-Chung Lin; Anil C. Kokaram (Visual Information Processing and Communication, 2016)

Geometrical Insights for Implicit Generative Modeling. - Léon Bottou; Martín Arjovsky; David Lopez-Paz; Maxime Oquab (Braverman Readings in Machine Learning, 2017)

Towards Principled Methods for Training Generative Adversarial Networks. - Martín Arjovsky; Léon Bottou (ICLR, 2017)

Adversarially Learned Inference. - Vincent Dumoulin; Ishmael Belghazi; Ben Poole; Alex Lamb; Martín Arjovsky; Olivier Mastropietro; Aaron C. Courville (ICLR (Poster), 2017)

Wasserstein Generative Adversarial Networks. - Martín Arjovsky; Soumith Chintala; Léon Bottou (ICML, 2017)

Improved Training of Wasserstein GANs. - Ishaan Gulrajani; Faruk Ahmed; Martín Arjovsky; Vincent Dumoulin; Aaron C. Courville (NIPS, 2017)

Wasserstein GAN. - Martín Arjovsky; Soumith Chintala; Léon Bottou (CoRR, 2017)

Invariant Risk Minimization. - Martín Arjovsky; Léon Bottou; Ishaan Gulrajani; David Lopez-Paz (CoRR, 2019)

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 (ICLR, 2020)

Symplectic Recurrent Neural Networks. - Zhengdao Chen; Jianyu Zhang; Martín Arjovsky; Léon Bottou (ICLR, 2020)

Low Distortion Block-Resampling with Spatially Stochastic Networks. - Sarah Jane Hong; Martín Arjovsky; Darryl Barnhart; Ian Thompson (NeurIPS, 2020)

Out of Distribution Generalization in Machine Learning. - Martín Arjovsky (2020)

Linear unit-tests for invariance discovery. - Benjamin Aubin; Agnieszka Slowik; Martín Arjovsky; Léon Bottou; David Lopez-Paz (CoRR, 2021)

Out of Distribution Generalization in Machine Learning. - Martín Arjovsky (CoRR, 2021)

Simple data balancing achieves competitive worst-group-accuracy. - Badr Youbi Idrissi; Martín Arjovsky; Mohammad Pezeshki; David Lopez-Paz (CLeaR, 2022)

Throwing Away Data Improves Worst-Class Error in Imbalanced Classification. - Martín Arjovsky; Kamalika Chaudhuri; David Lopez-Paz (CoRR, 2022)

Why does Throwing Away Data Improve Worst-Group Error? - Kamalika Chaudhuri; Kartik Ahuja; Martín Arjovsky; David Lopez-Paz (ICML, 2023)