263 citations · 269 across the 5 of their papers we have counts for
5 papers
SHREC 2025: Protein surface shape retrieval including electrostatic potential
Taher Yacoub, Camille Depenveiller, Atsushi Tatsuma +25
This SHREC 2025 track dedicated to protein surface shape retrieval involved 9 participating teams. We evaluated the performance in retrieval of 15 proposed methods on a large datas…
NewtonNet: A Newtonian message passing network for deep learning of interatomic potentials and forces
Mojtaba Haghighatlari, Jie Li, Xingyi Guan +10
We report a new deep learning message passing network that takes inspiration from Newton's equations of motion to learn interatomic potentials and forces. With the advantage of dir…
Fanpy: A Python Library for Prototyping Multideterminant Methods in Ab Initio Quantum Chemistry
Taewon David Kim, Michael Richer, Gabriela Sánchez-Díaz +4
Fanpy is a free and open-source Python library for developing and testing multideterminant wavefunctions and related ab initio methods in electronic structure theory. The main use…
Learning to Make Chemical Predictions: the Interplay of Feature Representation, Data, and Machine Learning Algorithms
Mojtaba Haghighatlari, Jie Li, Farnaz Heidar-Zadeh +3
Recently supervised machine learning has been ascending in providing new predictive approaches for chemical, biological and materials sciences applications. In this Perspective we…
Minimal Basis Iterative Stockholder: Atoms in Molecules for Force-Field Development
Toon Verstraelen, Steven Vandenbrande, Farnaz Heidar-Zadeh +4
Atomic partial charges appear in the Coulomb term of many force-field models and can be derived from electronic structure calculations with a myriad of atoms-in-molecules (AIM) met…