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The President handed over the decrees to the new professors |
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Among the new appointees were representatives from MU, details can be found here. |
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Students of DMS were awarded the Dean’s Award |
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Three Dean's Awards were awarded to Tomáš Pompa, Avinash Bansal and Jakub Záthurecký. More about the winners can be found in the article here. Congratulations! |
Special Session of the Central European Seminar In Celebration of Peter Michor’s 75th Birthday, June 6 – June 8, 2024 |
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SCI MUNI, DMS, building 8, lecture room M1, June 6 – June 8, 2024
This mini-conference is organized in honour of Peter Michor's, who recently got his dr.h.c from our university. All the speakers are Peter's former students, they display an exciting variety of topics and they come from world top places (Kings College, Florida, ETH Zurich, etc).
All the talks will be in M1 and you are all cordially invited.
See the (preliminary) programme.
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Dr. Sebastien Court - Designing the monodomain model with artificial neural networks - 22.5.2024 |
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On 22.5.2024 in the meeting room in the DMS from 2pm will take place this lecture:
Dr. Sebastien Court (Institut für Mathematik, Universität Innsbruck)
Designing the monodomain model with artificial neural networks
Abstract: We propose a data-driven method in order to identify the nonlinearity in the monodomain model. The monodomain model is a system coupling a semilinear parabolic PDE with an ODE, describing the time evolution of an electric potential. Our approach provides a general answer to the problem of selecting the model when studying phenomena related to cardiac electrophysiology: From measurements, instead of determining coefficients of a prescribed nonlinearity (like the FitzHugh-Nagumo model for instance), we design the nonlinearity itself, in the form of an artificial neural network (ANN), more specifically a feedforward residual network. The relevance of this approach relies on the approximation capacities of neural networks. Training the ANN corresponds to solving an identification problem constrained by the monodomain model so parameterized. We formulate this inverse problem as an optimal control problem, and provide mathematical analysis and derivation of optimality conditions for identifying the weights of the ANN. One of the difficulties comes from the lack of smoothness of activation functions which are classically used for training deep neural networks. We will also present numerical results that demonstrate the feasibility of the strategy proposed in this work. This is joint work with Prof. Karl Kunisch (RICAM & University of Graz).
Organizers: doc. RNDr. Lenka Přibylová, Ph.D. Department of Mathematics and Statistics, SCI MUNI the Nonlinear Dynamics Team https://science.math.muni.cz/ndteam/ Funding: European Horizon MSCA grant 101063853
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Last Updated on Monday, 20 May 2024 06:52 |
Innolec lectures - Pablo Emilio Verde - Bayesian Data Analysis with R |
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Lectures between 13.5. - 15.5.2024, DMS building (MP2 and seminar room, 2nd floor )
Bayesian Data Analysis with R
Dr. Pablo Emilio Verde, Heinrich Heine University Düsseldorf
13.5.2024:
- Introduction to Bayesian inference
- Bayesian statistical of simple statistical models
- Using R, MultiBUGS and JAGS for simple Bayesian models
13:00 - 14:00, MP2 14:00 - 18:00, seminar room, 2nd floor
14.5.2024:
- The role of prior distributions in Bayesian inference
- Bayesian analysis of multiple parameters models
- Bayesian analysis of regression models
- Introduction to Bayesian computations
08:00 - 12:00, 13:00 - 14:00, 15:00 - 18:00, seminar room, 2nd floor
15.5.2024:
- Introduction to Hierarchical Modeling
- Longitudinal data analysis
- Bayesian analysis of special models: models for missing data, non-parametric models
10:00 - 12:00, 13:00 - 17:00, seminar room, 2nd floor |
Last Updated on Tuesday, 07 May 2024 15:30 |
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