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2020 – today
- 2024
[j3]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)- [c7]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 - [c6]Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi:
Unsupervised Concept Discovery Mitigates Spurious Correlations. ICML 2024 - [c5]Gonçalo Mordido, Pranshu Malviya, Aristide Baratin, Sarath Chandar:
Lookbehind-SAM: k steps back, 1 step forward. ICML 2024 - [i17]Md Rifat Arefin, Yan Zhang, Aristide Baratin, Francesco Locatello, Irina Rish, Dianbo Liu, Kenji Kawaguchi:
Unsupervised Concept Discovery Mitigates Spurious Correlations. CoRR abs/2402.13368 (2024) - [i16]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 abs/2403.07688 (2024) - [i15]Anchit Jain, Rozhin Nobahari, Aristide Baratin, Stefano Sarao Mannelli:
Bias in Motion: Theoretical Insights into the Dynamics of Bias in SGD Training. CoRR abs/2405.18296 (2024) - [i14]Alexia Jolicoeur-Martineau, Aristide Baratin, Kisoo Kwon, Boris Knyazev, Yan Zhang:
Any-Property-Conditional Molecule Generation with Self-Criticism using Spanning Trees. CoRR abs/2407.09357 (2024) - 2023
- [j2]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) - [c4]Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien:
CrossSplit: Mitigating Label Noise Memorization through Data Splitting. ICML 2023: 16377-16392 - [i13]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 abs/2307.09638 (2023) - [i12]Gonçalo Mordido, Pranshu Malviya, Aristide Baratin, Sarath Chandar:
Lookbehind Optimizer: k steps back, 1 step forward. CoRR abs/2307.16704 (2023) - [i11]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 abs/2310.08513 (2023) - 2022
- [j1]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) - [i10]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 abs/2206.01251 (2022) - [i9]Thomas George, Guillaume Lajoie, Aristide Baratin:
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty. CoRR abs/2209.09658 (2022) - [i8]Jihye Kim, Aristide Baratin, Yan Zhang, Simon Lacoste-Julien:
CrossSplit: Mitigating Label Noise Memorization through Data Splitting. CoRR abs/2212.01674 (2022) - 2021
- [c3]Aristide Baratin, Thomas George, César Laurent, R. Devon Hjelm, Guillaume Lajoie, Pascal Vincent, Simon Lacoste-Julien:
Implicit Regularization via Neural Feature Alignment. AISTATS 2021: 2269-2277 - [i7]James Vuckovic, Aristide Baratin, Remi Tachet des Combes:
On the Regularity of Attention. CoRR abs/2102.05628 (2021) - 2020
- [i6]James Vuckovic, Aristide Baratin, Remi Tachet des Combes:
A Mathematical Theory of Attention. CoRR abs/2007.02876 (2020) - [i5]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 abs/2008.00938 (2020)
2010 – 2019
- 2019
- [c2]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: 5301-5310 - 2018
- [c1]Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeswar, Sherjil Ozair, Yoshua Bengio, R. Devon Hjelm, Aaron C. Courville:
Mutual Information Neural Estimation. ICML 2018: 530-539 - [i4]Akram Erraqabi, Aristide Baratin, Yoshua Bengio, Simon Lacoste-Julien:
A3T: Adversarially Augmented Adversarial Training. CoRR abs/1801.04055 (2018) - [i3]Ishmael Belghazi, Sai Rajeswar, Aristide Baratin, R. Devon Hjelm, Aaron C. Courville:
MINE: Mutual Information Neural Estimation. CoRR abs/1801.04062 (2018) - [i2]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 abs/1806.08734 (2018) - [i1]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 abs/1810.08591 (2018)
Coauthor Index
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last updated on 2024-10-09 21:27 CEST by the dblp team
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