Aristide Baratin

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 25

Top Topics

Mutual Information

Top Venues

Trans. Mach. Learn. Res.

Publications

Alexia Jolicoeur-Martineau, Aristide Baratin, Kisoo Kwon, Boris Knyazev, Yan Zhang
Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning Trees. CoRR (2024)
Anchit Jain, Rozhin Nobahari, Aristide Baratin, Stefano Sarao Mannelli
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training. CoRR (2024)
Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar
Promoting Exploration in Memory-Augmented Adam using Critical Momenta. Trans. Mach. Learn. Res. 2024 (2024)
Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie
How connectivity structure shapes rich and lazy learning in neural circuits. ICLR (2024)
Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi
Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR (2024)
Simon Dufort-Labbé, Pierluca D'Oro, Evgenii Nikishin, Razvan Pascanu, Pierre-Luc Bacon, Aristide Baratin
Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons. CoRR (2024)
Pranshu Malviya, Gonçalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar
Promoting Exploration in Memory-Augmented Adam using Critical Momenta. CoRR (2023)
Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron C. Courville, Alessandro Sordoni
Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods. Trans. Mach. Learn. Res. 2023 (2023)
Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien
CrossSplit: Mitigating Label Noise Memorization through Data Splitting. ICML (2023)
Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Shea-Brown, Guillaume Lajoie
How connectivity structure shapes rich and lazy learning in neural circuits. CoRR (2023)
Gonçalo Mordido, Pranshu Malviya, Aristide Baratin, Sarath Chandar
Lookbehind Optimizer: k steps back, 1 step forward. CoRR (2023)
Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron C. Courville, Alessandro Sordoni
Expressiveness and Learnability: A Unifying View for Evaluating Self-Supervised Learning. CoRR (2022)
Thomas George, Guillaume Lajoie, Aristide Baratin
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty. CoRR (2022)
Thomas George, Guillaume Lajoie, Aristide Baratin
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty. Trans. Mach. Learn. Res. 2022 (2022)
Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien
CrossSplit: Mitigating Label Noise Memorization through Data Splitting. CoRR (2022)
Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
Implicit Regularization via Neural Feature Alignment. AISTATS (2021)
James Vuckovic, Aristide Baratin, Remi Tachet des Combes
On the Regularity of Attention. CoRR (2021)
Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien
Implicit Regularization in Deep Learning: A View from Function Space. CoRR (2020)
James Vuckovic, Aristide Baratin, Remi Tachet des Combes
A Mathematical Theory of Attention. CoRR (2020)
Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville
On the Spectral Bias of Neural Networks. ICML (2019)
Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, R. Devon Hjelm, Aaron C. Courville
Mutual Information Neural Estimation. ICML (2018)
Brady Neal, Sarthak Mittal, Aristide Baratin, Vinayak Tantia, Matthew Scicluna, Simon Lacoste-Julien, Ioannis Mitliagkas
A Modern Take on the Bias-Variance Tradeoff in Neural Networks. CoRR (2018)
Ishmael Belghazi, Sai Rajeswar, Aristide Baratin, R. Devon Hjelm, Aaron C. Courville
MINE: Mutual Information Neural Estimation. CoRR (2018)
Nasim Rahaman, Devansh Arpit, Aristide Baratin, Felix Draxler, Min Lin, Fred A. Hamprecht, Yoshua Bengio, Aaron C. Courville
On the Spectral Bias of Deep Neural Networks. CoRR (2018)
Akram Erraqabi, Aristide Baratin, Yoshua Bengio, Simon Lacoste-Julien
A3T: Adversarially Augmented Adversarial Training. CoRR (2018)