Thermodynamic integration via Replica Exchange Hamiltonian Monte Carlo for faster sampling and model comparison

Reference : Thermodynamic integration via Replica Exchange Hamiltonian Monte Carlo for faster sam...


	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Multidisciplinary, general & others Engineering, computing & technology : Civil engineering
	Focus Areas :	Computational Sciences; Sustainable Development
	To cite this reference:	http://hdl.handle.net/10993/54462

Title :	Thermodynamic integration via Replica Exchange Hamiltonian Monte Carlo for faster sampling and model comparison
Language :	English
Author, co-author :	Mingo Ndiwago, Damian [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
	Nijzink, Remko []
	Ley, Christophe [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH) >]
	Schymanski, Stanislaus [Luxembourg Institute of Science and Technology (LIST) > Catchment and Ecohydrology Group (CAT), Environmental Research and Innovation (ERIN), Belvaux, Luxembourg]
	Hale, Jack [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
Publication date :	24-Apr-2023
Number of pages :	1
Peer reviewed :	No
Audience :	International
Event name :	EGU General Assembly
Event date :	23-04-2023 to 28-04-2023
Event organizer :	European Geosciences Union (EGU)
Event place (city) :	Vienna
Event country :	Austria
Keywords :	[en] Thermodynamic integration ; Replica Exchange Hamiltonian Monte Carlo ; rainfall-runoff
Funders :	Fonds National de la Recherche - FnR
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/54462
DOI :	10.5194/egusphere-egu23-2910
Other URL :	https://doi.org/10.5194/egusphere-egu23-2910
FnR project :	FnR ; FNR12252781 > Andreas Zilian > DRIVEN > Data-driven Computational Modelling And Applications > 01/09/2018 > 28/02/2025 > 2017

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