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@ONLINE{Wasmer:1020061,
author = {Wasmer, Johannes and Riebesell, Janosh},
othercontributors = {Evans, Matthew and Blaiszik, Ben},
title = {{B}est of {A}tomistic {M}achine {L}earning},
reportid = {FZJ-2023-05862},
year = {2023},
abstract = {A ranked list of awesome atomistic machine learning
projects.},
keywords = {ai4science (Other) / atomistic-machine-learning (Other) /
scientific-machine-learning (Other) / community-resource
(Other) / living-document (Other) / best-of-list (Other) /
awesome-list (Other) / molecular-dynamics (Other) /
density-functional-theory (Other) /
computational-materials-science (Other) /
computational-chemistry (Other) / quantum-chemistry (Other)
/ materials-discovery (Other) / materials-informatics
(Other) / drug-discovery (Other) / surrogate-models (Other)
/ electronic-structure (Other) / interatomic-potentials
(Other) / materials-datasets (Other) / chemistry-datasets
(Other)},
cin = {IAS-1 / PGI-1},
cid = {I:(DE-Juel1)IAS-1-20090406 / I:(DE-Juel1)PGI-1-20110106},
pnm = {5112 - Cross-Domain Algorithms, Tools, Methods Labs (ATMLs)
and Research Groups (POF4-511) / AIDAS - Joint Virtual
Laboratory for AI, Data Analytics and Scalable Simulation
$(aidas_20200731)$ / HDS LEE - Helmholtz School for Data
Science in Life, Earth and Energy (HDS LEE)
(HDS-LEE-20190612) / DFG project 491111487 -
Open-Access-Publikationskosten / 2022 - 2024 /
Forschungszentrum Jülich (OAPKFZJ) (491111487)},
pid = {G:(DE-HGF)POF4-5112 / $G:(DE-Juel-1)aidas_20200731$ /
G:(DE-Juel1)HDS-LEE-20190612 / G:(GEPRIS)491111487},
typ = {PUB:(DE-HGF)37},
doi = {10.5281/ZENODO.10430261},
url = {https://juser.fz-juelich.de/record/1020061},
}