607 citations · 1.8k across the 12 of their papers we have counts for
3 papers · 1 filter
Robust recognition and exploratory analysis of crystal structures via Bayesian deep learning
Andreas Leitherer, Angelo Ziletti, Luca M. Ghiringhelli
Due to their ability to recognize complex patterns, neural networks can drive a paradigm shift in the analysis of materials science data. Here, we introduce ARISE, a crystal-struct…
NOMAD 2018 Kaggle Competition: Solving Materials Science Challenges Through Crowd Sourcing
Christopher Sutton, Luca M. Ghiringhelli, Takenori Yamamoto +7
Machine learning (ML) is increasingly used in the field of materials science, where statistical estimates of computed properties are employed to rapidly examine the chemical space…
Insightful classification of crystal structures using deep learning
A. Ziletti, D. Kumar, M. Scheffler +1
Computational methods that automatically extract knowledge from data are critical for enabling data-driven materials science. A reliable identification of lattice symmetry is a cru…