activity
20232026
most citedRoadmap on machine learning glassy dynamics

38 citations · 72 across the 8 of their papers we have counts for

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Showing cond-mat.softShow all

5 papers · 1 filter

cond-mat.soft2026

Collective adaptation to time-dependent targets for active Brownian particles

Gerhard Jung, Eric Bertin

We consider a minimal model of active agents which collectively learn to reach a target macroscopic state via a decentralized adaptation process. Agents are modeled as active Brown…

cond-mat.soft2025★ 1 cited

Numerical investigation of the equilibrium Kauzmann transition in a two-dimensional atomistic glass

Gerhard Jung, Misaki Ozawa, Giulio Biroli +1

Dense liquids gradually transform into non-equilibrium amorphous solids as they pass through the experimental glass transition. Experimentally, ergodicity is lost because measureme…

cond-mat.soft2024★ 11 cited

Normalizing flows as an enhanced sampling method for atomistic supercooled liquids

Gerhard Jung, Giulio Biroli, Ludovic Berthier

Normalizing flows can transform a simple prior probability distribution into a more complex target distribution. Here, we evaluate the ability and efficiency of generative machine…

cond-mat.soft2023★ 38 cited

Roadmap on machine learning glassy dynamics

Gerhard Jung, Rinske M. Alkemade, Victor Bapst +10

Unraveling the connections between microscopic structure, emergent physical properties, and slow dynamics has long been a challenge when studying the glass transition. The absence…

cond-mat.soft2023★ 19 cited

Dynamic heterogeneity at the experimental glass transition predicted by transferable machine learning

Gerhard Jung, Giulio Biroli, Ludovic Berthier

We develop a transferable machine learning model which predicts structural relaxation from amorphous supercooled liquid structures. The trained networks are able to predict dynamic…