Using replica exchange Hamiltonian Monte Carlo and thermodynamic integration for comparison of dynamic rainfall-runoff models

Reference : Using replica exchange Hamiltonian Monte Carlo and thermodynamic integration for comp...


	Document type :	Scientific congresses, symposiums and conference proceedings : Unpublished conference
	Discipline(s) :	Physical, chemical, mathematical & earth Sciences : Mathematics Engineering, computing & technology : Multidisciplinary, general & others
	Focus Areas :	Computational Sciences
	To cite this reference:	http://hdl.handle.net/10993/54843

Title :	Using replica exchange Hamiltonian Monte Carlo and thermodynamic integration for comparison of dynamic rainfall-runoff models
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 [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > >]
	Hale, Jack [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Engineering (DoE) >]
Publication date :	25-Jan-2023
Peer reviewed :	No
On invitation :	Yes
Audience :	International
Event name :	Luxembourg-Waseda Conference on Modelling and Inference for Complex Data
Event date :	23-01-2023 to 25-01-2023
Event organizer :	Department of Mathematics, University of Luxembourg, SanDAL and WASEDA University
Event place (city) :	Belval
Event country :	Luxembourg
Keywords :	[en] Dynamic models ; rainfall-runoff models ; Replica Exchange Hamiltonian Monte Carlo ; thermodynamic integration
Target :	Researchers ; Professionals ; Students ; General public
Permalink :	http://hdl.handle.net/10993/54843
FnR project :	FnR ; FNR12252781 > Andreas Zilian > DRIVEN > Data-driven Computational Modelling And Applications > 01/09/2018 > 28/02/2025 > 2017

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