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)

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)

Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias. - Stéphane d'Ascoli; Levent Sagun; Giulio Biroli; Joan Bruna (NeurIPS, 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)

Conditioned Query Generation for Task-Oriented Dialogue Systems. - Stéphane d'Ascoli; Alice Coucke; Francesco Caltagirone; Alexandre Caulier; Marc Lelarge (CoRR, 2019)

Double Trouble in Double Descent: Bias and Variance(s) in the Lazy Regime. - Stéphane d'Ascoli; Maria Refinetti; Giulio Biroli; Florent Krzakala (ICML, 2020)

Triple descent and the two kinds of overfitting: where & why do they appear? - Stéphane d'Ascoli; Levent Sagun; Giulio Biroli (NeurIPS, 2020)

Conditioned Text Generation with Transfer for Closed-Domain Dialogue Systems. - Stéphane d'Ascoli; Alice Coucke; Francesco Caltagirone; Alexandre Caulier; Marc Lelarge (SLSP, 2020)

The dynamics of learning with feedback alignment. - Maria Refinetti; Stéphane d'Ascoli; Ruben Ohana; Sebastian Goldt (CoRR, 2020)

Align, then memorise: the dynamics of learning with feedback alignment. - Maria Refinetti; Stéphane d'Ascoli; Ruben Ohana; Sebastian Goldt (ICML, 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 (ICML, 2021)

On the interplay between data structure and loss function in classification problems. - Stéphane d'Ascoli; Marylou Gabrié; Levent Sagun; Giulio Biroli (NeurIPS, 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)

Transformed CNNs: recasting pre-trained convolutional layers with self-attention. - Stéphane d'Ascoli; Levent Sagun; Giulio Biroli; Ari Morcos (CoRR, 2021)

Deep symbolic regression for recurrence prediction. - Stéphane d'Ascoli; Pierre-Alexandre Kamienny; Guillaume Lample; François Charton (ICML, 2022)

End-to-end Symbolic Regression with Transformers. - Pierre-Alexandre Kamienny; Stéphane d'Ascoli; Guillaume Lample; François Charton (NeurIPS, 2022)

Deep Symbolic Regression for Recurrent Sequences. - Stéphane d'Ascoli; Pierre-Alexandre Kamienny; Guillaume Lample; François Charton (CoRR, 2022)

Optimal learning rate schedules in high-dimensional non-convex optimization problems. - Stéphane d'Ascoli; Maria Refinetti; Giulio Biroli (CoRR, 2022)

Length Generalization in Arithmetic Transformers. - Samy Jelassi; Stéphane d'Ascoli; Carles Domingo-Enrich; Yuhuai Wu; Yuanzhi Li; François Charton (CoRR, 2023)

Boolformer: Symbolic Regression of Logic Functions with Transformers. - Stéphane d'Ascoli; Samy Bengio; Josh M. Susskind; Emmanuel Abbe (CoRR, 2023)

Elucidating the Hierarchical Nature of Behavior with Masked Autoencoders. - Lucas Stoffl; Andy Bonnetto; Stéphane d'Ascoli; Alexander Mathis (ECCV (64), 2024)

ODEFormer: Symbolic Regression of Dynamical Systems with Transformers. - Stéphane d'Ascoli; Sören Becker; Philippe Schwaller; Alexander Mathis; Niki Kilbertus (ICLR, 2024)

A Polar coordinate system represents syntax in large language models. - Pablo Diego-Simón; Stéphane d'Ascoli; Emmanuel Chemla; Yair Lakretz; Jean-Remi King (NeurIPS, 2024)

Decoding individual words from non-invasive brain recordings across 723 participants. - Stéphane d'Ascoli; Corentin Bel; Jérémy Rapin; Hubert J. Banville; Yohann Benchetrit; Christophe Pallier; Jean-Rémi King (CoRR, 2024)

Scaling laws for decoding images from brain activity. - Hubert J. Banville; Yohann Benchetrit; Stéphane d'Ascoli; Jérémy Rapin; Jean-Rémi King (CoRR, 2025)

Brain-to-Text Decoding: A Non-invasive Approach via Typing. - Jarod Lévy; Mingfang Zhang 006; Svetlana Pinet; Jérémy Rapin; Hubert J. Banville; Stéphane d'Ascoli; Jean-Rémi King (CoRR, 2025)

TRIBE: TRImodal Brain Encoder for whole-brain fMRI response prediction. - Stéphane d'Ascoli; Jérémy Rapin; Yohann Benchetrit; Hubert J. Banville; Jean-Rémi King (CoRR, 2025)