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Akira Yamaguchi

1 paper here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author1

Across the 1 of 1 paper where every author was matched, so the position is known.

fields
  • cond-mat.dis-nn1
ORCID 0000-0002-3550-4239
same name
  • Akira Yamaguchi — 3 papers
  • Akira Yamaguchi — 1 paper, h 2
  • Akira Yamaguchi — 1 paper, h 4
  • Akira Yamaguchi — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

most citedA cost-effective strategy of enhancing machine learning potentials by transfer learning from a multicomponent dataset on ænet-PyTorch

1 citations · 1 across the 1 of their papers we have counts for

collaborators

1 paper

cond-mat.dis-nn2024★ 1 cited

A cost-effective strategy of enhancing machine learning potentials by transfer learning from a multicomponent dataset on ænet-PyTorch

An Niza El Aisnadaa, Kajjana Boonpalit Robin van der Kruit, Koen M. Draijer +4

Machine learning potentials (MLPs) offer efficient and accurate material simulations, but constructing the reference ab initio database remains a significant challenge, particularl…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.