136 citations · 434 across the 22 of their papers we have counts for
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cond-mat.soft2022★ 68 cited
Predicting dynamic heterogeneity in glass-forming liquids by physics-inspired machine learning
Gerhard Jung, Giulio Biroli, Ludovic Berthier
We introduce GlassMLP, a machine learning framework using physics-inspired structural input to predict the long-time dynamics in deeply supercooled liquids. We apply this deep neur…
cond-mat.soft2022★ 8 cited
Structural properties of liquids in extreme confinement
Gerhard Jung, Thomas Franosch
We simulate a hard-sphere liquid in confined geometry where the separation of the two parallel, hard walls is smaller than two particle diameters. By systematically reducing the wa…