Mutual Information Neural Estimation. - Mohamed Ishmael Belghazi; Aristide Baratin; Sai Rajeswar; Sherjil Ozair; Yoshua Bengio; R. Devon Hjelm; Aaron C. Courville (ICML, 2018)

A3T: Adversarially Augmented Adversarial Training. - Akram Erraqabi; Aristide Baratin; Yoshua Bengio; Simon Lacoste-Julien (CoRR, 2018)

MINE: Mutual Information Neural Estimation. - Ishmael Belghazi; Sai Rajeswar; Aristide Baratin; R. Devon Hjelm; Aaron C. Courville (CoRR, 2018)

On the Spectral Bias of Deep Neural Networks. - Nasim Rahaman; Devansh Arpit; Aristide Baratin; Felix Draxler; Min Lin; Fred A. Hamprecht; Yoshua Bengio; Aaron C. Courville (CoRR, 2018)

A Modern Take on the Bias-Variance Tradeoff in Neural Networks. - Brady Neal; Sarthak Mittal; Aristide Baratin; Vinayak Tantia; Matthew Scicluna; Simon Lacoste-Julien; Ioannis Mitliagkas (CoRR, 2018)

On the Spectral Bias of Neural Networks. - Nasim Rahaman; Aristide Baratin; Devansh Arpit; Felix Draxler; Min Lin; Fred A. Hamprecht; Yoshua Bengio; Aaron C. Courville (ICML, 2019)

A Mathematical Theory of Attention. - James Vuckovic; Aristide Baratin; Remi Tachet des Combes (CoRR, 2020)

Implicit Regularization in Deep Learning: A View from Function Space. - Aristide Baratin; Thomas George; César Laurent; R. Devon Hjelm; Guillaume Lajoie; Pascal Vincent; Simon Lacoste-Julien (CoRR, 2020)

Implicit Regularization via Neural Feature Alignment. - Aristide Baratin; Thomas George; César Laurent; R. Devon Hjelm; Guillaume Lajoie; Pascal Vincent; Simon Lacoste-Julien (AISTATS, 2021)

On the Regularity of Attention. - James Vuckovic; Aristide Baratin; Remi Tachet des Combes (CoRR, 2021)

Expressiveness and Learnability: A Unifying View for Evaluating Self-Supervised Learning. - Yuchen Lu; Zhen Liu 019; Aristide Baratin; Romain Laroche; Aaron C. Courville; Alessandro Sordoni (CoRR, 2022)

Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty. - Thomas George; Guillaume Lajoie; Aristide Baratin (Trans. Mach. Learn. Res., 2022)

CrossSplit: Mitigating Label Noise Memorization through Data Splitting. - Jihye Kim; Aristide Baratin; Yan Zhang; Simon Lacoste-Julien (ICML, 2023)

Lookbehind Optimizer: k steps back, 1 step forward. - Gonçalo Mordido; Pranshu Malviya; Aristide Baratin; Sarath Chandar (CoRR, 2023)

Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods. - Yuchen Lu; Zhen Liu 019; Aristide Baratin; Romain Laroche; Aaron C. Courville; Alessandro Sordoni (Trans. Mach. Learn. Res., 2023)

How connectivity structure shapes rich and lazy learning in neural circuits. - Yuhan Helena Liu; Aristide Baratin; Jonathan Cornford; Stefan Mihalas; Eric Shea-Brown; Guillaume Lajoie (ICLR, 2024)

Unsupervised Concept Discovery Mitigates Spurious Correlations. - Md Rifat Arefin; Yan Zhang; Aristide Baratin; Francesco Locatello; Irina Rish; Dianbo Liu; Kenji Kawaguchi (ICML, 2024)

Lookbehind-SAM: k steps back, 1 step forward. - Gonçalo Mordido; Pranshu Malviya; Aristide Baratin; Sarath Chandar (ICML, 2024)

Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training. - Anchit Jain; Rozhin Nobahari; Aristide Baratin; Stefano Sarao Mannelli (NeurIPS, 2024)

Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons. - Simon Dufort-Labbé; Pierluca D'Oro; Evgenii Nikishin; Razvan Pascanu; Pierre-Luc Bacon; Aristide Baratin (CoRR, 2024)

Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning Trees. - Alexia Jolicoeur-Martineau; Aristide Baratin; Kisoo Kwon; Boris Knyazev 001; Yan Zhang (CoRR, 2024)

Torque-Aware Momentum. - Pranshu Malviya; Gonçalo Mordido; Aristide Baratin; Reza Babanezhad Harikandeh; Gintare Karolina Dziugaite; Razvan Pascanu; Sarath Chandar (CoRR, 2024)

Promoting Exploration in Memory-Augmented Adam using Critical Momenta. - Pranshu Malviya; Gonçalo Mordido; Aristide Baratin; Reza Babanezhad Harikandeh; Jerry Huang; Simon Lacoste-Julien; Razvan Pascanu; Sarath Chandar (Trans. Mach. Learn. Res., 2024)

Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons. - Simon Dufort-Labbé; Pierluca D'Oro; Evgenii Nikishin; Irina Rish; Pierre-Luc Bacon; Razvan Pascanu; Aristide Baratin (Trans. Mach. Learn. Res., 2025)

Generating π-Functional Molecules Using STGG+ with Active Learning. - Alexia Jolicoeur-Martineau; Yan Zhang; Boris Knyazev 001; Aristide Baratin; Cheng-Hao Liu (CoRR, 2025)