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Mittwoch | 16.30 Uhr | Scientific Computing meets Neuroscience @ UHEI Statistical Approach for Parameter Identification of Reaction-Diffusion Models Dr. Alexey Kazarnikov, Heidelberg University, Institute for Applied Mathematics Mathematical models allow establishing a connection between observed data and a hypothetical underlying mechanism. However, a given biological process can robustly produce qualitatively and quantitatively similar patterns, which however always differ, depending on small variations in the initial state of the process. A statistical algorithm for parameter identification of reaction-diffusion systems is suggested that needs steady-state pattern data only, without knowledge of initial values or transient data. This is the situation often faced in experimental work. Model parameters that are able to fit given pattern data well enough are quantified by Bayesian sampling methods. In addition, this provides a tool allowing comparison of different mechanisms by checking how well a specific model can be fitted to the data produced by a model based on a Adresse - - - 0 - Homepage Veranstaltung https://typo.iwr.uni-heidelberg.de/events/iwr-colloquium/ Veranstalter Interdisciplinary Center for Scientific Computing Homepage Veranstalter https://typo.iwr.uni-heidelberg.de/home/ Kontakt Kontakt URL https://www1.iwr.uni-heidelberg.de/iwr/public/people/de/3217 Alle Termine der Veranstaltung 'Scientific Computing meets Neuroscience @ UHEI': The IWR Colloquium serves as a platform for the interdisciplinary dialogue which characterizes the field of scientific computing. Mittwoch, 16. Dezember 2020, 16.30 Uhr From Bistable Neurons to Recurrent Neuronal Networks Dr. Rebecca Mease, Heidelberg University, Medical Faculty Heidelberg, Institute of Physiology and Pathophysiology Mittwoch, 20. Januar 2021, 16.30 Uhr Scientific Computing meets Neuroscience @ UHEI Mittwoch, 03. Februar 2021, 16.30 Uhr Statistical Approach for Parameter Identification of Reaction-Diffusion Models Dr. Alexey Kazarnikov, Heidelberg University, Institute for Applied Mathematics Mittwoch, 10. Februar 2021, 15.30 Uhr Unsupervised Behavior Analysis and Magnification using Deep Learning (uBAM) Prof. Dr. Björn Ommer, Heidelberg University, Interdisciplinary Center for Scientific Computing |