Record link: 
http://hdl.handle.net/20.500.12708/218509
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Title: 
Machine Learning for Quantum Many-Body Physics: Efficient Representation of Vertex Functions
en
Citation: 
Hepp, S., Andergassen, S., & Springer, D. (2025, August 20). Machine Learning for Quantum Many-Body Physics: Efficient Representation of Vertex Functions [Poster Presentation]. Joint Annual Meeting of the Austrian and Swiss Physical Society (ÖPG and SPS 2025), Wien, Austria. http://hdl.handle.net/20.500.12708/218509
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Publication Type: 
Presentation - Poster Presentation
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Language: 
English
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Authors: 
Hepp, Sebastian 
Andergassen, Sabine 
Springer, Daniel 
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Organisational Unit: 
E194-06 - Forschungsbereich Machine Learning 
E138-02 - Forschungsbereich Correlations: Theory and Experiments 
E056-23 - Fachbereich Innovative Combinations and Applications of AI and ML (iCAIML) 
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Date (published): 
20-Aug-2025
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Event name: 
Joint Annual Meeting of the Austrian and Swiss Physical Society (ÖPG and SPS 2025) 
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Event date: 
18-Aug-2025 - 22-Aug-2025
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Event place: 
Wien, Austria
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Keywords: 
Machine Learning; Quantum Many-Body Physics
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Research facilities: 
Vienna Scientific Cluster 
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Additional information: 
https://portal-cdn.scnat.ch/asset/abd88cf4-825e-561c-8497-64a781a211f1/SPG-%C3%96PG-2025_Poster_web.pdf?b=5dd55fa7-267c-537a-bfb7-0b74fd1cde07&v=3aecdff9-a9de-58e5-a6c2-cd4ebde306d5_0&s=OquUJoRmTT4yEmKSbjIgRzUaSqjDGMndNXdeTZhdtRTwx8_8AiAklMeGG5PPD7OJaOKpAusfmDTJ4beqLY5bjfBkfQbtUuBfbacDRs2GblkQxZJQIL3Sh9msAUM64nA7C0j3fkeRQQ29b-MwS1HRokNS4e_NOh8T4DrnmDi-HOI ---- https://oepg-sps-meetingvienna2025.univie.ac.at/
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Research Areas: 
Quantum Many-body Systems Physics: 25%
Computer Engineering and Software-Intensive Systems: 75%
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Science Branch: 
1020 - Informatik: 75%
1030 - Physik, Astronomie: 25%
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