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Autotuning T-PaiNN: Enabling Data-Efficient GNN Interatomic Potential Development via Classical-to-Quantum Transfer Learning

Fuente: arXiv

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Dettagli Bibliografici
Autori principali:	Pelletier, Vivienne, Bhat, Vedant, Rivera, Daniel J., Wilson, Steven A., Muhich, Christopher L.
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Chemical Physics Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

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