Publications

Stéphane d' Ascoli, Levent Sagun, Giulio Biroli (2020). Triple descent and the two kinds of overfitting: where & why do they appear?. Advances in Neural Information Processing Systems.

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Mario Geiger, Arthur Jacot, Stefano Spigler, Franck Gabriel, Levent Sagun, Stéphane d’Ascoli, Giulio Biroli, Clément Hongler, Matthieu Wyart (2020). Scaling description of generalization with number of parameters in deep learning. Journal of Statistical Mechanics: Theory and Experiment.

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Stéphane d'Ascoli, Maria Refinetti, Giulio Biroli, Florent Krzakala (2020). Double Trouble in Double Descent: Bias and Variance (s) in the Lazy Regime. International Conference on Machine Learning.

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Mario Geiger, Stefano Spigler, Stéphane d'Ascoli, Levent Sagun, Marco Baity-Jesi, Giulio Biroli, Matthieu Wyart (2019). Jamming transition as a paradigm to understand the loss landscape of deep neural networks. Physical Review E.

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Stéphane d'Ascoli, Levent Sagun, Giulio Biroli, Joan Bruna (2019). Finding the Needle in the Haystack with Convolutions: on the benefits of architectural bias. Advances in Neural Information Processing Systems.

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Stéphane d'Ascoli, Alice Coucke, Francesco Caltagirone, Alexandre Caulier, Marc Lelarge (2019). Conditioned Query Generation for Task-Oriented Dialogue Systems. arXiv preprint arXiv:1911.03698.

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S Spigler, M Geiger, S d’Ascoli, L Sagun, G Biroli, M Wyart (2019). A jamming transition from under-to over-parametrization affects generalization in deep learning. Journal of Physics A: Mathematical and Theoretical.

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Stéphane d’Ascoli, Scott C Noble, Dennis B Bowen, Manuela Campanelli, Julian H Krolik, Vassilios Mewes (2018). Electromagnetic Emission from Supermassive Binary Black Holes Approaching Merger. The Astrophysical Journal.

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