M12. Bayesian, Variational, and Stochastic Methods for Uncertainty Quantification in Optimization and Inverse Problems
The primary objective of this mini-symposium is to bring together distinguished experts and aspiring researchers to discuss recent advances and emerging challenges in the rapidly evolving field of uncertainty quantification. This symposium will provide a platform for exchanging ideas, fostering collaborations, and exploring innovative methodologies that address uncertainty in complex systems.
The mini-symposium will cover a broad spectrum of topics, including Bayesian methodologies, robust optimization, variational approaches, and a variety of stochastic techniques such as stochastic approximation and sampling-based strategies. Special emphasis will be placed on their applications to optimization and inverse problems arising in diverse scientific and engineering models, including imaging, material science, fluid dynamics, and data-driven modeling. By bridging theory and applications, this symposium aims to highlight cutting-edge developments and inspire future research directions in uncertainty quantification.
Organizers:
Caroline Geiersbach, University of Klagenfurt, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
Akhtar A. Khan, Rochester Institute of Technology, USA, This email address is being protected from spambots. You need JavaScript enabled to view it.
Pablo Pedregal Tercero, University of Castilla-La Mancha, Spain, This email address is being protected from spambots. You need JavaScript enabled to view it.
Christiane Tammer, Martin-Luther-University of Halle-Wittenberg, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.
Invited Speakers:
Christian Aarset, France, This email address is being protected from spambots. You need JavaScript enabled to view it.
Optimal experimental design for passive imaging
Andrea Aspri, Università degli Studi di Milano Statale, Italy, This email address is being protected from spambots. You need JavaScript enabled to view it.
Neural operators for the Dirichlet-to-Neumann map
Simona Beresova, Institute of Geonics, Czech Republic, simona.beresova@ugn.
Surrogate-accelerated MCMC for Bayesian inference with Gaussian random field materials
Ana Carpio, Universidad Complutense de Madrid, Spain, This email address is being protected from spambots. You need JavaScript enabled to view it.
Uncertainty quantification in shear elastography
Neil Chada, City University of Hong Kong, China, This email address is being protected from spambots. You need JavaScript enabled to view it.
Multilevel stochastic derivative-free bilevel optimization
Patrizia Daniele, University of Catania, Italy, This email address is being protected from spambots. You need JavaScript enabled to view it.
A variational optimization framework for sustainable parcel locker networks
Oliver Ernst, Chemnitz University of Technology, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.
Regularization Is not MAP, and neither Is it Bayesian: common misconceptions in UQ for inverse problems
Caroline Geiersbach, University of Klagenfurt, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
A maximum probability problem in optimal control
Neven Hadžić, University of Zagreb, Croatia, This email address is being protected from spambots. You need JavaScript enabled to view it.
A probabilistic approach to modeling biofouling development on marine vessel hulls
Helmut Harbrecht, Universität Basel, Switzerland, This email address is being protected from spambots. You need JavaScript enabled to view it.
Shape optimization under constraints on the probability of a quadratic functional to exceed a given threshold
Akhtar A. Khan, Rochester Institute of Technology, USA. This email address is being protected from spambots. You need JavaScript enabled to view it.
Estimating random coefficients in mixed variational problems: applications to stochastic elasticity imaging
Stefan Kindermann, Johannes Kepler University Linz, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
Parameter identification for a contact problem
Victor A. Kovtunenko, University of Graz, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
Semi-smooth optimization methods for solution of contact and dynamic problems
Kang Liu, Universite Bourgogne Europe, France, This email address is being protected from spambots. You need JavaScript enabled to view it.
From backward hest equation to generative models
Diana-Elena Mirciu, University of Klagenfurt, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it.
On primal-dual algorithms for ill-posed problems
Anna Ochal, Jagiellonian University, Poland, This email address is being protected from spambots. You need JavaScript enabled to view it.
Optimal control problem for elliptic hemivariational inequalities
Pablo Pedregal, Universidad de Castilla-La Mancha, Spain, This email address is being protected from spambots. You need JavaScript enabled to view it.
DeepONet: a deep learning–based framework for approximating linear and nonlinear operators
Laurent Seppecher, École Centrale Lyon, France, This email address is being protected from spambots. You need JavaScript enabled to view it.
Interferometric LASSO for stable wave source inversion in random media
Alexandra Smirnova, Georgia State University, USA, This email address is being protected from spambots. You need JavaScript enabled to view it.
Infectious disease modeling: optimization under uncertainty
Hans-Jörg Starkloff, Technische Universität Bergakademie Freiberg, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it.
Measurability issues for inverse stochastic elliptic variational problems
Christiane Tammer, Martin-Luther-University of Halle-Wittenberg, Germany, christiane.tammer@mathematik.
Nonsmooth nearly convex optimization problems and applications in robustness
Chaoli Yao, Hainan University, P.R, China, This email address is being protected from spambots. You need JavaScript enabled to view it.
Image regularity conditions based on nonconvex separation with application
Adrian Zălinescu, Alexandru I. Cuza University of Iaşi, Romania, This email address is being protected from spambots. You need JavaScript enabled to view it.
Kolmogorov-type PDEs arising from BSDEs with delay: A comparison of solution concepts