A strategic roadmap for an atomistic machine-learning ecosystem
Data-driven machine learning (ML) techniques have become an essential tool in many domains of science. Their application to atomistic simulations of matter is particularly widespread and impactful. This success is due largely to the existence of a well-developed and established physics-based modeling framework, ranging...
Jörg Behler, Michele Ceriotti, Cecilia Clementi et al.
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