7 citations · 7 across the 2 of their papers we have counts for
2 papers
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…
cs.LG2022★ 7 cited
Message Passing Neural Networks for Hypergraphs
Sajjad Heydari, Lorenzo Livi
Hypergraph representations are both more efficient and better suited to describe data characterized by relations between two or more objects. In this work, we present a new graph n…