7 citations · 19 across the 19 of their papers we have counts for
3 papers · 1 filter
Predicting Lattice Phonon Vibrational Frequencies Using Deep Graph Neural Networks
Nghia Nguyen, Steph-Yves Louis, Lai Wei +3
Lattice vibration frequencies are related to many important materials properties such as thermal and electrical conductivity as well as superconductivity. However, computational ca…
Scalable deeper graph neural networks for high-performance materials property prediction
Sadman Sadeed Omee, Steph-Yves Louis, Nihang Fu +5
Machine learning (ML) based materials discovery has emerged as one of the most promising approaches for breakthroughs in materials science. While heuristic knowledge based descript…
MaterialsAtlas.org: A Materials Informatics Web App Platform for Materials Discovery and Survey of State-of-the-Art
Jianjun Hu, Stanislav Stefanov, Yuqi Song +4
The availability and easy access of large scale experimental and computational materials data have enabled the emergence of accelerated development of algorithms and models for mat…