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1
gridds : a data science toolkit for energy grid machine ..:
, In:
Proceedings of the Thirteenth ACM International Conference on Future Energy Systems
,
Ladd, Alexander
;
Chakraborty, Indrasis
- p. 542-551 , 2022
Link:
https://dl.acm.org/doi/10.1145/3538637.3539614
RT T1 <cTitle>Proceedings of the Thirteenth ACM International Conference on Future Energy Systems</cTitle>: T1 <Title>gridds : a data science toolkit for energy grid machine learning</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3539614&Exemplar=1&LAN=DE A1 Ladd, Alexander A1 Chakraborty, Indrasis PB ACM YR 2022 K1 Computing methodologies K1 Machine learning K1 Learning paradigms K1 Supervised learning K1 Supervised learning by regression K1 Unsupervised learning K1 Cluster analysis K1 Applied computing K1 Physical sciences and engineering K1 Mathematics and statistics K1 Machine learning approaches K1 Learning in probabilistic graphical models K1 Latent variable models K1 Neural networks SP 542 OP 551 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3538637.3539614 DO https://dl.acm.org/doi/10.1145/3538637.3539614 SF ELIB - SuUB Bremen
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