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Posts by Giulio Biroli

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🚀 « #IA à Paris. Un an après le sommet, construire l’avenir »
En amont du prochain rdv international en Inde, PSL et @ipparis.bsky.social, avec HEC Paris, unissent leurs forces pour un après-midi de réflexion de haut niveau, le 9 février au @college-de-france.fr.
Infos 👉 psl.eu/agenda/lia-p...

2 months ago 3 4 1 0
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Yielding and plasticity in amorphous solids - Nature Reviews Physics Amorphous materials yield through complex, history-dependent mechanisms involving localized defects and avalanche dynamics. This Review unifies theoretical advances across glasses, foams, biological t...

Ludovic Berthier, @giuliobiroli.bsky.social‬, Lisa Manning & Francesco Zamponi give a perspective on yielding and plasticity in amorphous solids, emphasizing the importance of a unified approach to studying the response to deformation and the yielding instability
www.nature.com/articles/s42...

11 months ago 2 2 0 0
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1/ Happy to share my first accepted paper as a PhD student at Meta and ENS, Paris which I will present at @iclr-conf.bsky.social:

📚 Our work proposes difFOCI, a novel rank-based objective for ✨better feature learning✨

In collab with David Lopez-Paz, @giuliobiroli.bsky.social and Levent Sagun!

1 year ago 3 1 1 0
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The program of the 2025 Beg Rohu Summer School is out! See www.phys.ens.psl.eu/en/cours/beg... with fantastic lecturers: Agliari, King, @yann-lecun.bsky.social, Mallat, Mézard, Murugan on topics at the frontiers of statistical physics, machine learning and neuroscience

1 year ago 9 1 0 0
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IA versus ordinateur quantique : un combat très physique Dans la course à la résolution des problèmes fondamentaux de physique et de chimie, l’intelligence artificielle et l’informatique quantique sont les deux champions en lice. Pour mieux en comprendre le...

For the french-speaking friends: an article in @lemonde.fr "AI versus quantum computing : a very physical fight!" also featuring excerpts from an interview I had with David Larousserie www.lemonde.fr/sciences/art...

1 year ago 9 2 0 0
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ML methods are an asset in analysing numerically glassy dynamics - a notoriously difficult physics problem. If you want to know more on recent results and future directions, check out our "Roadmap on machine learning glassy dynamics", just appeared on Nature Reviews www.nature.com/articles/s42...

1 year ago 9 2 0 1

A happy author discovering the first hard copies

1 year ago 96 16 3 1