Record link: 
http://hdl.handle.net/20.500.12708/229493
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Title: 
A Markov chain Monte Carlo approach for Bayesian inverse problems with limited data
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Citation: 
Taghizadeh, L., & Schneider, F. (2026). A Markov chain Monte Carlo approach for Bayesian inverse problems with limited data. In Abstracts of the 12th International Conference : Inverse Problems: Modeling and Simulation (pp. 241–241).
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Publication Type: 
Inproceedings - Abstract Book Contribution
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Language: 
English
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Authors: 
Taghizadeh, Leila 
Schneider, Fabian 
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Organisational Unit: 
E101-03-2 - Forschungsgruppe Unsicherheitsquantifizierung 
E101-02-3 - Forschungsgruppe Computational PDEs 
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Published in: 
Abstracts of the 12th International Conference : Inverse Problems: Modeling and Simulation 
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Date (published): 
1-Jun-2026
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Event name: 
The 12th International Conference "Inverse Problems: Modeling and Simulation" (IPMS 2026) 
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Event date: 
31-May-2026 - 5-Jun-2026
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Event place: 
Malta
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Number of Pages: 
1
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Keywords: 
Infinite-dimensional Bayesian inverse problem; Infinite-dimensional Bayesian inverse problem; Infinite-dimensional Bayesian inverse problem; xsemiconductor devices
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Project title: 
Rechnerische Unsicherheitsquantifizierung in Nanotechnologie: V 1000-N (FWF - Österr. Wissenschaftsfonds) 
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Research Areas: 
Mathematical and Algorithmic Foundations: 100%
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Science Branch: 
1010 - Mathematik: 100%
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Appears in Collections:
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