most citedPeering inside the black box: Learning the relevance of many-body functions in Neural Network potentials

7 citations · 7 across the 1 of their papers we have counts for

collaborators

2 papers

physics.comp-ph2024★ 7 cited

Peering inside the black box: Learning the relevance of many-body functions in Neural Network potentials

Klara Bonneau, Jonas Lederer, Clark Templeton +3

Machine learned potentials are becoming a popular tool to define an effective energy model for complex systems, either incorporating electronic structure effects at the atomistic r…

q-bio.NC2023

Getting aligned on representational alignment

Ilia Sucholutsky, Lukas Muttenthaler, Adrian Weller +30

Biological and artificial information processing systems form representations of the world that they can use to categorize, reason, plan, navigate, and make decisions. How can we m…