{"user_id":"81513","department":[{"_id":"101"}],"author":[{"full_name":"Klus, Stefan","last_name":"Klus","first_name":"Stefan"},{"full_name":"Gelß, Patrick","last_name":"Gelß","first_name":"Patrick"},{"first_name":"Feliks","id":"81513","orcid":"0000-0003-2444-7889","full_name":"Nüske, Feliks","last_name":"Nüske"},{"first_name":"Frank","last_name":"Noé","full_name":"Noé, Frank"}],"year":"2021","title":"Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry","language":[{"iso":"eng"}],"publication":"Machine Learning: Science and Technology","_id":"24170","publication_identifier":{"issn":["2632-2153"]},"date_updated":"2022-01-06T06:56:08Z","citation":{"mla":"Klus, Stefan, et al. “Symmetric and Antisymmetric Kernels for Machine Learning Problems in Quantum Physics and Chemistry.” Machine Learning: Science and Technology, 045016, 2021, doi:10.1088/2632-2153/ac14ad.","apa":"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, Article 045016. https://doi.org/10.1088/2632-2153/ac14ad","bibtex":"@article{Klus_Gelß_Nüske_Noé_2021, title={Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry}, DOI={10.1088/2632-2153/ac14ad}, number={045016}, journal={Machine Learning: Science and Technology}, author={Klus, Stefan and Gelß, Patrick and Nüske, Feliks and Noé, Frank}, year={2021} }","short":"S. Klus, P. Gelß, F. Nüske, F. Noé, Machine Learning: Science and Technology (2021).","ieee":"S. Klus, P. Gelß, F. Nüske, and F. Noé, “Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry,” Machine Learning: Science and Technology, Art. no. 045016, 2021, doi: 10.1088/2632-2153/ac14ad.","ama":"Klus S, Gelß P, Nüske F, Noé F. Symmetric and antisymmetric kernels for machine learning problems in quantum physics and chemistry. Machine Learning: Science and Technology. Published online 2021. doi:10.1088/2632-2153/ac14ad","chicago":"Klus, Stefan, Patrick Gelß, Feliks Nüske, and Frank Noé. “Symmetric and Antisymmetric Kernels for Machine Learning Problems in Quantum Physics and Chemistry.” Machine Learning: Science and Technology, 2021. https://doi.org/10.1088/2632-2153/ac14ad."},"article_number":"045016","status":"public","type":"journal_article","doi":"10.1088/2632-2153/ac14ad","publication_status":"published","date_created":"2021-09-12T08:52:57Z"}