Advancing extrapolative predictions of material properties through learning to learn using extrapolative episodic training

Abstract Recent advancements in machine learning have demonstrated its potential to significantly accelerate the discovery of new materials. Central to this progress is the development of rapidly computable property predictors, which allow identifying novel materials with the desired properties from...

Full description

Saved in:
Bibliographic Details
Main Authors: Kohei Noda, Araki Wakiuchi, Yoshihiro Hayashi, Ryo Yoshida
Format: Article
Language:English
Published: Nature Portfolio 2025-02-01
Series:Communications Materials
Online Access:https://doi.org/10.1038/s43246-025-00754-x
Tags: Add Tag
No Tags, Be the first to tag this record!