Symmetric and antisymmetric kernels for machine learning problems in quantum 
physics and chemistry

Klus, Stefan; Gelß, Patrick; Nüske, Feliks; Noé, Frank

doi:10.1088/2632-2153/ac14ad

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Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry

Klus, S., Gelß, P., Nüske, F., & Noé, F. (2021). Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Machine Learning: Science and Technology, 2: 045016. doi:10.1088/2632-2153/ac14ad.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000A-30F6-A Version Permalink: https://hdl.handle.net/21.11116/0000-000C-F222-C

Genre: Journal Article

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Creators:
Klus, Stefan¹, Author
Gelß, Patrick¹, Author
Nüske, Feliks¹, Author
Noé, Frank¹, Author

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1External Organizations, ou_persistent22

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Dates: Published Online: 2021-08-06Date issued: 2021

Publication Status: Issued

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Identifiers: DOI: 10.1088/2632-2153/ac14ad

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Title: Machine Learning: Science and Technology

Source Genre: Journal

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Pages: - Volume / Issue: 2 Sequence Number: 045016 Start / End Page: - Identifier: ISSN: 2632-2153