Martín Arjovsky

Publication Activity (10 Years)

Years Active: 2015-2023
Publications (10 Years): 27

Top Topics

Risk Minimization

Class Discrimination

Recurrent Neural Networks

Top Venues

Publications

Kamalika Chaudhuri, Kartik Ahuja, Martín Arjovsky, David Lopez-Paz
Why does Throwing Away Data Improve Worst-Group Error? ICML (2023)
Martín Arjovsky, Kamalika Chaudhuri, David Lopez-Paz
Throwing Away Data Improves Worst-Class Error in Imbalanced Classification. CoRR (2022)
Badr Youbi Idrissi, Martín Arjovsky, Mohammad Pezeshki, David Lopez-Paz
Simple data balancing achieves competitive worst-group-accuracy. CLeaR (2022)
Benjamin Aubin, Agnieszka Slowik, Martín Arjovsky, Léon Bottou, David Lopez-Paz
Linear unit-tests for invariance discovery. CoRR (2021)
Badr Youbi Idrissi, Martín Arjovsky, Mohammad Pezeshki, David Lopez-Paz
Simple data balancing achieves competitive worst-group-accuracy. CoRR (2021)
Martín Arjovsky
Out of Distribution Generalization in Machine Learning. CoRR (2021)
Sarah Jane Hong, Martín Arjovsky, Darryl Barnhart, Ian Thompson
Low Distortion Block-Resampling with Spatially Stochastic Networks. NeurIPS (2020)
Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andrew Bolt, Charles Blundell
Never Give Up: Learning Directed Exploration Strategies. CoRR (2020)
Zhengdao Chen, Jianyu Zhang, Martín Arjovsky, Léon Bottou
Symplectic Recurrent Neural Networks. ICLR (2020)
Adrià Puigdomènech Badia, Pablo Sprechmann, Alex Vitvitskyi, Zhaohan Daniel Guo, Bilal Piot, Steven Kapturowski, Olivier Tieleman, Martín Arjovsky, Alexander Pritzel, Andrew Bolt, Charles Blundell
Never Give Up: Learning Directed Exploration Strategies. ICLR (2020)
Sarah Jane Hong, Martín Arjovsky, Ian Thompson, Darryl Barnhart
Low Distortion Block-Resampling with Spatially Stochastic Networks. CoRR (2020)
Zhengdao Chen, Jianyu Zhang, Martín Arjovsky, Léon Bottou
Symplectic Recurrent Neural Networks. CoRR (2019)
Martín Arjovsky, Léon Bottou, Ishaan Gulrajani, David Lopez-Paz
Invariant Risk Minimization. CoRR (2019)
Martín Arjovsky, Soumith Chintala, Léon Bottou
Wasserstein Generative Adversarial Networks. ICML (2017)
Martín Arjovsky, Léon Bottou
Towards Principled Methods for Training Generative Adversarial Networks. CoRR (2017)
Martín Arjovsky, Léon Bottou
Towards Principled Methods for Training Generative Adversarial Networks. ICLR (2017)
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
Adversarially Learned Inference. ICLR (Poster) (2017)
Léon Bottou, Martín Arjovsky, David Lopez-Paz, Maxime Oquab
Geometrical Insights for Implicit Generative Modeling. Braverman Readings in Machine Learning (2017)
Ishaan Gulrajani, Faruk Ahmed, Martín Arjovsky, Vincent Dumoulin, Aaron C. Courville
Improved Training of Wasserstein GANs. NIPS (2017)
Martín Arjovsky, Soumith Chintala, Léon Bottou
Wasserstein GAN. CoRR (2017)
Léon Bottou, Martín Arjovsky, David Lopez-Paz, Maxime Oquab
Geometrical Insights for Implicit Generative Modeling. CoRR (2017)
Ishaan Gulrajani, Faruk Ahmed, Martín Arjovsky, Vincent Dumoulin, Aaron C. Courville
Improved Training of Wasserstein GANs. CoRR (2017)
Martín Arjovsky, Amar Shah, Yoshua Bengio
Unitary Evolution Recurrent Neural Networks. ICML (2016)
Vincent Dumoulin, Ishmael Belghazi, Ben Poole, Alex Lamb, Martín Arjovsky, Olivier Mastropietro, Aaron C. Courville
Adversarially Learned Inference. CoRR (2016)
Michele Covell, Martín Arjovsky, Yao-Chung Lin, Anil C. Kokaram
Optimizing Transcoder Quality Targets Using a Neural Network with an Embedded Bitrate Model. Visual Information Processing and Communication (2016)
Martín Arjovsky
Saddle-free Hessian-free optimization for Deep Learning. CoRR (2015)
Martín Arjovsky, Amar Shah, Yoshua Bengio
Unitary Evolution Recurrent Neural Networks. CoRR (2015)