Stéphane d'Ascoli

According to our database, Stéphane d'Ascoli authored at least 21 papers between 2018 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

ODEFormer: Symbolic Regression of Dynamical Systems with Transformers.

Stéphane d'Ascoli, Sören Becker, Alexander Mathis, Philippe Schwaller, Niki Kilbertus

CoRR, 2023

Boolformer: Symbolic Regression of Logic Functions with Transformers.

Stéphane d'Ascoli, Samy Bengio, Josh M. Susskind, Emmanuel Abbe

CoRR, 2023

Length Generalization in Arithmetic Transformers.

Samy Jelassi, Stéphane d'Ascoli, Carles Domingo-Enrich, Yuhuai Wu, Yuanzhi Li, François Charton

CoRR, 2023

2022

Optimal learning rate schedules in high-dimensional non-convex optimization problems.

Stéphane d'Ascoli, Maria Refinetti, Giulio Biroli

CoRR, 2022

Deep Symbolic Regression for Recurrent Sequences.

Stéphane d'Ascoli, Pierre-Alexandre Kamienny, Guillaume Lample, François Charton

CoRR, 2022

End-to-end Symbolic Regression with Transformers.

Pierre-Alexandre Kamienny, Stéphane d'Ascoli, Guillaume Lample, François Charton

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Deep symbolic regression for recurrence prediction.

Stéphane d'Ascoli, Pierre-Alexandre Kamienny, Guillaume Lample, François Charton

Proceedings of the International Conference on Machine Learning, 2022

2021

Transformed CNNs: recasting pre-trained convolutional layers with self-attention.

Stéphane d'Ascoli, Levent Sagun, Giulio Biroli, Ari Morcos

CoRR, 2021

More data or more parameters? Investigating the effect of data structure on generalization.

Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli

CoRR, 2021

On the interplay between data structure and loss function in classification problems.

Stéphane d'Ascoli, Marylou Gabrié, Levent Sagun, Giulio Biroli

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

ConViT: Improving Vision Transformers with Soft Convolutional Inductive Biases.

Stéphane d'Ascoli, Hugo Touvron, Matthew L. Leavitt, Ari S. Morcos, Giulio Biroli, Levent Sagun

Proceedings of the 38th International Conference on Machine Learning, 2021

Align, then memorise: the dynamics of learning with feedback alignment.

Maria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

The dynamics of learning with feedback alignment.

Maria Refinetti, Stéphane d'Ascoli, Ruben Ohana, Sebastian Goldt

CoRR, 2020

Conditioned Text Generation with Transfer for Closed-Domain Dialogue Systems.

Stéphane d'Ascoli, Alice Coucke, Francesco Caltagirone, Alexandre Caulier, Marc Lelarge

Proceedings of the Statistical Language and Speech Processing, 2020

Triple descent and the two kinds of overfitting: where & why do they appear?

Stéphane d'Ascoli, Levent Sagun, Giulio Biroli

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime.

Stéphane d'Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Conditioned Query Generation for Task-Oriented Dialogue Systems.

Stéphane d'Ascoli, Alice Coucke, Francesco Caltagirone, Alexandre Caulier, Marc Lelarge

CoRR, 2019

Scaling description of generalization with number of parameters in deep learning.

Mario Geiger, Arthur Jacot, Stefano Spigler, Franck Gabriel, Levent Sagun, Stéphane d'Ascoli, Giulio Biroli, Clément Hongler, Matthieu Wyart

CoRR, 2019

Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias.

Stéphane d'Ascoli, Levent Sagun, Giulio Biroli, Joan Bruna

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018

A jamming transition from under- to over-parametrization affects loss landscape and generalization.

Stefano Spigler, Mario Geiger, Stéphane d'Ascoli, Levent Sagun, Giulio Biroli, Matthieu Wyart

CoRR, 2018

The jamming transition as a paradigm to understand the loss landscape of deep neural networks.

Mario Geiger, Stefano Spigler, Stéphane d'Ascoli, Levent Sagun, Marco Baity-Jesi, Giulio Biroli, Matthieu Wyart

CoRR, 2018