1.8k citations · 5.3k across the 59 of their papers we have counts for
59 papers
Machine-learning octet -type binary compounds across chemical space with domain knowledge of the interatomic bond
Rohan Kumar, Mariano D. Forti, Aakash A. Naik +2
The prediction of the structural stability of octet -type binary compounds is a classical materials informatics problem. The challenge is to capture the relative stability of 4…
Roadmap on Advancements of the FHI-aims Software Package
Joseph W. Abbott, Carlos Mera Acosta, Alaa Akkoush +203
Electronic-structure theory is the foundation of the description of materials including multiscale modeling of their properties and functions. Obviously, without sufficient accurac…
A high-performance and portable implementation of the SISSO method for CPUs and GPUs
Sebastian Eibl, Yi Yao, Matthias Scheffler +3
SISSO (sure-independence screening and sparsifying operator) is an artificial intelligence (AI) method based on symbolic regression and compressed sensing widely used in materials…
How big is Big Data?
Daniel T. Speckhard, Tim Bechtel, Luca M. Ghiringhelli +3
Big data has ushered in a new wave of predictive power using machine learning models. In this work, we assess what {\it big} means in the context of typical materials-science machi…
Combining genetic algorithm and compressed sensing for features and operators selection in symbolic regression
Aliaksei Mazheika, Sergey V. Levchenko, Luca M. Ghiringhelli
Symbolic-inference methods have recently found a broad application in materials science. In particular, the Sure-Independence Screening and Sparsifying Operator (SISSO) performs sy…
Roadmap on Data-Centric Materials Science
Stefan Bauer, Peter Benner, Tristan Bereau +58
Science is and always has been based on data, but the terms "data-centric" and the "4th paradigm of" materials research indicate a radical change in how information is retrieved, h…