Baratin, Aristide

19 publications

TMLR 2025 Any-Property-Conditional Molecule Generation with Self-Criticism Using Spanning Trees Alexia Jolicoeur-Martineau, Aristide Baratin, Kisoo Kwon, Boris Knyazev, Yan Zhang

ICLRW 2025 Generating $\pi$-Functional Molecules Using STGG+ with Active Learning Alexia Jolicoeur-Martineau, Yan Zhang, Boris Knyazev, Aristide Baratin, Cheng-Hao Liu

TMLR 2025 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

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

NeurIPSW 2024 Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training Anchit Jain, Rozhin Nobahari, Aristide Baratin, Stefano Sarao Mannelli

ICLR 2024 How Connectivity Structure Shapes Rich and Lazy Learning in Neural Circuits Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford, Stefan Mihalas, Eric Todd SheaBrown, Guillaume Lajoie

NeurIPSW 2024 How Learning Rates Shape Neural Network Focus: Insights from Example Ranking Ekaterina Lobacheva, Keller Jordan, Aristide Baratin, Nicolas Le Roux

ICML 2024 Lookbehind-SAM: K Steps Back, 1 Step Forward Goncalo Mordido, Pranshu Malviya, Aristide Baratin, Sarath Chandar

TMLR 2024 Promoting Exploration in Memory-Augmented Adam Using Critical Momenta Pranshu Malviya, Goncalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar

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

ICML 2023 CrossSplit: Mitigating Label Noise Memorization Through Data Splitting Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien

TMLR 2023 Using Representation Expressiveness and Learnability to Evaluate Self-Supervised Learning Methods Yuchen Lu, Zhen Liu, Aristide Baratin, Romain Laroche, Aaron Courville, Alessandro Sordoni

TMLR 2022 Lazy vs Hasty: Linearization in Deep Networks Impacts Learning Schedule Based on Example Difficulty Thomas George, Guillaume Lajoie, Aristide Baratin

ICMLW 2022 Lazy vs Hasty: Linearization in Deep Networks Impacts Learning Schedule Based on Example Difficulty Thomas George, Guillaume Lajoie, Aristide Baratin

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

NeurIPSW 2020 Implicit Regularization via Neural Feature Alignment Aristide Baratin, Thomas George, César Laurent, R Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien

ICMLW 2019 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

ICML 2019 On the Spectral Bias of Neural Networks Nasim Rahaman, Aristide Baratin, Devansh Arpit, Felix Draxler, Min Lin, Fred Hamprecht, Yoshua Bengio, Aaron Courville

ICML 2018 Mutual Information Neural Estimation Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeshwar, Sherjil Ozair, Yoshua Bengio, Aaron Courville, Devon Hjelm