most citedHEroBM: a deep equivariant graph neural network for universal backmapping from coarse-grained to all-atom representations

4 citations · 6 across the 3 of their papers we have counts for

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physics.chem-ph2024★ 4 cited

HEroBM: a deep equivariant graph neural network for universal backmapping from coarse-grained to all-atom representations

Daniele Angioletti, Stefano Raniolo, Vittorio Limongelli

Molecular simulations have assumed a paramount role in the fields of chemistry, biology, and material sciences, being able to capture the intricate dynamic properties of systems. W…

physics.chem-ph2022

Transferring Chemical and Energetic Knowledge Between Molecular Systems with Machine Learning

Sajjad Heydari, Stefano Raniolo, Lorenzo Livi +1

Predicting structural and energetic properties of a molecular system is one of the fundamental tasks in molecular simulations, and it has use cases in chemistry, biology, and medic…