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Stéphane d'Ascoli
Stéphane d'Ascoli
AI4science fellow at EPFL, Lausanne
Verified email at epfl.ch - Homepage
Title
Cited by
Cited by
Year
Convit: Improving vision transformers with soft convolutional inductive biases
S d’Ascoli, H Touvron, ML Leavitt, AS Morcos, G Biroli, L Sagun
International Conference on Machine Learning, 2286-2296, 2021
6902021
Scaling description of generalization with number of parameters in deep learning
M Geiger, A Jacot, S Spigler, F Gabriel, L Sagun, S d’Ascoli, G Biroli, ...
Journal of Statistical Mechanics: Theory and Experiment 2020 (2), 023401, 2020
2052020
Jamming transition as a paradigm to understand the loss landscape of deep neural networks
M Geiger, S Spigler, S d'Ascoli, L Sagun, M Baity-Jesi, G Biroli, M Wyart
Physical Review E 100 (1), 012115, 2019
1602019
Double trouble in double descent: Bias and variance (s) in the lazy regime
S d’Ascoli, M Refinetti, G Biroli, F Krzakala
International Conference on Machine Learning, 2280-2290, 2020
1412020
A jamming transition from under-to over-parametrization affects generalization in deep learning
S Spigler, M Geiger, S d’Ascoli, L Sagun, G Biroli, M Wyart
Journal of Physics A: Mathematical and Theoretical 52 (47), 474001, 2019
1302019
Electromagnetic Emission from Supermassive Binary Black Holes Approaching Merger
S d'Ascoli, SC Noble, DB Bowen, M Campanelli, JH Krolik, V Mewes
The Astrophysical Journal 865 (2), 2018
1002018
End-to-end symbolic regression with transformers
PA Kamienny, S d'Ascoli, G Lample, F Charton
Advances in Neural Information Processing Systems, 8754-8765, 2022
902022
Triple descent and the two kinds of overfitting: Where & why do they appear?
S d'Ascoli, L Sagun, G Biroli
Advances in Neural Information Processing Systems 33, 3058-3069, 2020
882020
A jamming transition from under-to over-parametrization affects loss landscape and generalization
S Spigler, M Geiger, S d'Ascoli, L Sagun, G Biroli, M Wyart
NeurIPS 2018 Workshop « Science of Deep Leaning Meets Engineering », 2019
662019
Deep symbolic regression for recurrence prediction
S d’Ascoli, PA Kamienny, G Lample, F Charton
International Conference on Machine Learning, 4520-4536, 2022
52*2022
Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias
S d'Ascoli, L Sagun, G Biroli, J Bruna
Advances in Neural Information Processing Systems, 9334-9345, 2019
372019
Align, then memorise: the dynamics of learning with feedback alignment
M Refinetti, S d’Ascoli, R Ohana, S Goldt
International Conference on Machine Learning, 8925-8935, 2021
232021
On the interplay between data structure and loss function in classification problems
S d'Ascoli, M Gabrié, L Sagun, G Biroli
Advances in Neural Information Processing Systems 34, 2021
16*2021
Length generalization in arithmetic transformers
S Jelassi, S d'Ascoli, C Domingo-Enrich, Y Wu, Y Li, F Charton
arXiv preprint arXiv:2306.15400, 2023
152023
The dynamics of learning with feedback alignment
M Refinetti, S d’Ascoli, R Ohana, S Goldt
Journal of Physics A, 2020
142020
Transformed CNNs: recasting pre-trained convolutional layers with self-attention
S d'Ascoli, L Sagun, G Biroli, A Morcos
arXiv preprint arXiv:2106.05795, 2021
52021
Conditioned Text Generation with Transfer for Closed-Domain Dialogue Systems
S d’Ascoli, A Coucke, F Caltagirone, A Caulier, M Lelarge
International Conference on Statistical Language and Speech Processing, 23-34, 2020
5*2020
Optimal learning rate schedules in high-dimensional non-convex optimization problems
S d'Ascoli, M Refinetti, G Biroli
arXiv preprint arXiv:2202.04509, 2022
42022
Comprendre la révolution de l'intelligence artificielle
S d'Ascoli
First, 2020
42020
Odeformer: Symbolic regression of dynamical systems with transformers
S d'Ascoli, S Becker, A Mathis, P Schwaller, N Kilbertus
arXiv preprint arXiv:2310.05573, 2023
32023
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