Research Seminar on Mathematical Optimization / Non-smooth Variational Problems and Operator Equations   📅

Institute
Head
Michael Hintermüller
Number of talks
60
Comment
Currently past talks are not included because the homepage lists some talks without a clear date.
Mon, 23.03.26 at 14:30
WIAS ESH and online
Well-posedness and optimal control of a PDE-ODE spatial-network model on metric graphs and sub-domains
Abstract. Mathematical modeling of dynamics on metric graphs arises in various contexts, from epidemic dynamics to chemical transport in fractured media. Diffusion processes and interactions within complex topological structures pose significant analytical challenges. In practical scenarios, effective intervention strategies are also critical. In this work, we analyze a coupled PDE-ODE system defined on a hybrid structure. The model is formulated as a nonlinear system with junction conditions that capture diffusion in subdomains, along edges, and at vertices. The well-posedness of the system, including the existence, uniqueness, and regularity of solutions, is established via Galerkin approximations and energy estimates. Building on these coupled dynamics, we extend our approach to optimal control. In this framework, a quadratic cost functional penalizes deviations of the state variables from desired targets while accounting for the energetic cost of control actions. Our analysis demonstrates that the state-to-control mapping is Fréchet differentiable, and we derive the corresponding linearized system and adjoint system, along with the first-order optimality conditions.
Fri, 27.02.26 at 15:00
WIAS ESH and online
Structural optimization with convex non-differentiable anisotropy: Application to 3D printing
Abstract. 3D printing is an umbrella term for a set of technologies that manufacture highly intricate and complex designs that are not feasible with traditional die-casting or injection molding methods. But despite their popularization in recent years, several limitations prevent further integration of 3D printing into existing production lines. One recurring issue relates to overhangs, which are regions of the constructed object that when placed in a certain orientation extend outwards without any underlying support. Some of these overhangs can deform under their own weight and, if not supported from below, present a risk in damaging the printed object. Conventional wisdom from practitioners says that overhangs whose outer normal makes an angle greater than 135 degrees with the upwards vertical direction should be supported from below with scaffolding. These are then removed after a successful print, but increase the material and processing costs. Another remedy is to modify the design to be self-supporting as much as possible without compromising its intended functionality. In this talk we consider the latter within a structural topology optimization framework. Extending previous studies with a linear elasticity model, we realize an overhang angle constraint with the help of a convex anisotropic perimeter functional, and study the corresponding optimal control problem. Earlier studies with non-convex functionals lead to instabilities termed the "dripping effect", which can be suppressed under our proposed framework. Numerical examples are provided to demonstrate how we discourage designs that develop overhangs not respecting the angle constraint. It turns out that for our approach we have to work with non-differentiable functionals, and thus we turn to subdifferential calculus to derive the first order optimality conditions. If time permits we will touch on a related aspect of 4D printing that builds on these technologies to create designs capable of changing their shape and functionalities via external stimulus. This is a joint work with Harald Garcke (Regensburg), Robert Nurnberg (Trento) and Andrea Signori (Pavia).
Thu, 12.02.26 at 15:30
WIAS R406 and online
Constrained Mean-Field Games under Uncertainty
Abstract. We consider mean-field games (MFGs) under uncertainty arising from constrained optimal control problems governed by stochastic ordinary differential equations (SODEs). Starting from a finite N-player game of risk-neutral agents whose individual dynamics are described by linear time-invariant ODEs with random parameters, we establish well-posedness of the SODE and prove existence and uniqueness results of optimal solutions. A characterization of optimal controls is obtained via first-order necessary optimality conditions. Passing to the limit as N goes to infinity, the mean-field interaction term is approximated by a probability measure, leading to a limiting MFG formulation. We show the existence of a mean-field equilibrium and prove that it induces an ε-Nash equilibrium for the finite N-game, as N tends to infinity. This provides a rigorous justification of the mean-field approximation for a large population of agents under uncertainty.
Thu, 29.01.26 at 10:00
WIAS R405 and online
Learning Elliptic Variational Inequalities via Weak Min-Max Formulations
Abstract. In this talk, we will present a novel weak adversarial framework for solving obstacle problems using neural networks. By reformulating the problem via (generalised) regularised gap functions into a natural min-max structure, we create a setting well suited to learning based approaches. We will outline the error analysis, highlighting both discretisation and statistical errors. Then, we will explain how parametrising the solution and test functions as neural networks allows us to solve the resulting min-max problem using a modified gradient descent-ascent method. Numerical experiments illustrate the robustness of the method. We will conclude by discussing current limitations, open problems, and future challenges of the approach.
Tue, 02.12.25 at 10:00
Online via Zoom
Convergence rates of regularized quasi-Newton methods without strong convexity
Abstract. In this talk, we discuss the convergence rates of the cubic regularized proximal quasi-Newton method for solving non-smooth additive composite problems that satisfy the Kurdyka-Łojasiewicz (KL) property with respect to some desingularizing function, instead of relying on strong convexity. In particular, when the objective function is smooth and satisfies the Polyak-Łojasiewicz (PL) inequality, the algorithm attains a global superlinear convergence. Additionally, we introduce two practical and computationally efficient variants based on limited-memory quasi-Newton techniques.
Wed, 02.07.25 at 11:00
WIAS R411 HVP5-7 ...
Existence and duality theory for linear-growth variational problems with measures
Abstract. We consider functionals F with linear growth in the gradient variable coupled with a non-linear integral term respect to a (possibly signed) Radon measure on bounded domains in Rn. After achieving a generalized parametric lower-semicontinuity result, we then provide necessary and sufficient conditions for existence of BV-minimizers of F, discussing typical examples as well as limit cases. In parallel, we determine the corresponding dual maximization problem set in the class of divergence-measure vector fields and we reformulate the optimality relations in terms of a refined version of Anzellotti's pairing between measures and functions. By introducing a suitable notion of solutions to the Euler-Lagrange equation associated to F, we then demonstrate that our BV theory is complete and it provides natural extension to the Sobolev model. The seminar is based on joint work with Thomas Schmidt (Universität Hamburg).
Tue, 20.05.25 at 14:00
WIAS R411 HVP5-7 ...
Quantum circuit simulation with a localized dynamic time-dependent variational principle
Abstract. We introduce a novel tensor network simulation method for quantum circuits that addresses key limitations inherent in the widely used time-evolving block decimation algorithm (TEBD). ... Benchmarking against conventional TEBD simulations demonstrates that our local TDVP simulation scheme achieves improved numerical stability, lower bond dimensions with at least the fidelity of TEBD, paving the way for more reliable large-scale quantum circuit simulations.
Tue, 11.03.25 at 14:00
WIAS HVP5-7 R411 ...
Multi-objective optimization with linear hyperbolic PDE constraints: generalized Nash equilibrium problems and gas market applications
Abstract. The concept of Nash equilibrium is fundamental to a wide range of applications, spanning fields from particle mechanics to micro and macroeconomics. ... Finally, we present some recent results on the existence and characterization of equilibria, emphasizing optimality conditions as a framework for understanding such solutions.
Tue, 17.12.24
WIAS HVP5-7 R411 ...
Multi-objective optimization with linear hyperbolic PDE constraints: generalized Nash equilibrium problems and gas market applications
Abstract. The concept of Nash equilibrium is fundamental to a wide range of applications, spanning fields from particle mechanics to micro and macroeconomics. However, much of the existing literature focuses on finite-dimensional settings. In this seminar, we draw on energy markets coupled with transport dynamics to motivate the study of multi-objective optimization problems with hyperbolic PDE constraints. We will explore the core ideas and challenges posed by generalized Nash equilibrium problems, particularly those related to dimensionality and regularity. Finally, we present some recent results on the existence and characterization of equilibria, emphasizing optimality conditions as a framework for understanding such solutions.
Tue, 26.11.24 at 14:00
WIAS HVP5-7 R411 ...
Hybrid physics-informed neural network based dual-scale solver and its applications to learning-informed upscaling
Abstract. Inspired by the Liquid Composite Molding process for fiber-reinforced composites and its associated multiscale fluid flow structure, we present a novel framework for optimizing physics-informed neural networks (PINNs) constrained by partial differential equations (PDEs), with applications to dual-scale PDE systems. ... In this talk, we present the application setting, mathematical model, and highlights of its analysis, as well as outline perspectives on developing optimization algorithms for the hybrid framework in the infinite-dimensional setting.
Thu, 14.11.24 at 10:00
WIAS HVP5-7 R411 ...
Free boundary problems as limits of a bulk-surface model for receptor-ligand interactions on evolving domains
Abstract. We derive various free boundary problems as reaction or singular limits of a coupled bulk-surface reaction-diffusion system on an evolving domain. ... In this talk, I will discuss the modelling, sketch the analysis, show some numerical simulations and finish with some open questions. Based on a joint work with Charlie Elliott, Chandrasekhar Venkataraman and Diogo Caetano.
Tue, 22.10.24 at 14:00
WIAS HVP5-7 R411 ...
A semismooth Newton method for obstacle-type quasivariational inequalities
Abstract. Quasivariational inequalities (QVIs) are ubiquitous but, in particular, arise in PDE-constrained optimization in cases where the constraint set depends on the solution itself. ... We will see that the solver enjoys favourable properties such as local superlinear convergence and mesh independence.
Tue, 10.09.24 at 10:30
WIAS HVP11 R 3.13...
Verifying the equivalence or non-equivalence of quantum circuits with tensor networks
Abstract. The development of quantum computers and algorithms is currently rapidly accelerating ... by using tensor network techniques to verify the equivalence or non-equivalence of quantum circuits in order to detect errors that may occur during the many steps of this process.
Wed, 26.06.24 at 14:00
WIAS HVP5-7 R411 ...
Model predictive control for generalized Nash Equilibrium problems
Abstract. We study model predictive control (MPC) schemes for non-cooperative dynamic games. ... Passing to a limit, we identify a suitable Lyapunov function for MPC schemes based on the original GNEPs.
Wed, 29.05.24 at 10:00
WIAS HVP5-7 R411 ...
Quantum noise characterization with a tensor network quantum jump method
Abstract. In this talk, we will discuss a novel approach to characterizing the noise in noisy quantum circuits through the Tensorized Quantum Jump Method (TJM). ... makes this method a new approach to characterizing quantum noise in large systems by learning the corresponding noise parameters.
Mon, 27.05.24 at 14:00
WIAS ESH and online
Robust Multilevel Training of Artificial Neural Networks
Abstract. In this talk, we will introduce a multilevel optimizier for training of an artificial neural network. We are particularly interested in neural networks to learn the hidden physical law or nonlinear mapping from the given data using algebraic multigrid strategies. And we would like to give some further insight into the potential of multilevel optimization methods in the end.
Tue, 07.05.24 at 14:30
WIAS HVP5-7 R411 ...
Rate independent evolutions: some basics, some progress
Abstract. We discuss some elementary rate independent evolutions, in particular the stop and the play, and offer remarks on the historical development. We also elaborate on issues concerning related optimal control problems.
Wed, 21.02.24 at 14:00
WIAS HVP5-7 R411 ...
Computing multiple solutions of topology optimization problems
Abstract. Topology optimization finds the optimal material distribution of a fluid or solid in a domain, subject to PDE and volume constraints. ... Underpinning the algorithm is the deflation mechanism. Deflation prevents a Newton-like solver from converging to a solution that has already been discovered.
Tue, 19.12.23 at 14:00
WIAS ESH and online
Maximal parabolic regularity for the treatment of real world problems
Abstract. This is a series of three lectures on non-smooth problems, the first dedicated to elliptic ones and the third to parabolic ones. ... we show that second order divergence operators satisfy this property even if the domain is highly non-smooth, the coefficient function is only bounded, measurable and elliptic and the boundary conditions are mixed
Mon, 18.12.23 at 14:00
Online talk and W...
Super-resolved Lasso
Abstract. Super-resolution of pointwise sources is of utmost importance in various areas of imaging sciences. ... A notable advantage of SR-Lasso is its theoretical properties, akin to grid-less methods. Given a separation condition on the sources and a restriction on the shift magnitude outside the grid, SR-Lasso precisely estimates the correct number of sources.
Mon, 20.11.23 at 14:00
WIAS R406 and online
Regularity for non-smooth elliptic problems II
Abstract. This is a series of three lectures on non-smooth problems, the first dedicated to elliptic ones and the third to parabolic ones. ... we show that second order divergence operators satisfy this property even if the domain is highly non-smooth, the coefficient function is only bounded, measurable and elliptic and the boundary conditions are mixed
Tue, 24.10.23 at 10:00
WIAS ESH and online
Analysis of a variational contact problem arising in thermoelasticity
Abstract. We study a model of a thermoforming process involving a membrane and a mould as implicit obstacle problems. ... Under certain contraction conditions, we also show a uniqueness result. This is based on a joint paper with Jose-Francisco Rodrigues (Lisbon, Portugal) and Carlos N. Rautenberg (Virginia, USA).
Tue, 17.10.23 at 14:00
WIAS ESH and online
Regularity for non-smooth elliptic problems I
Abstract. This is a series of three lectures on non-smooth problems, the first dedicated to elliptic ones and the third to parabolic ones. ... we show that second order divergence operators satisfy this property even if the domain is highly non-smooth, the coefficient function is only bounded, measurable and elliptic and the boundary conditions are mixed
Thu, 12.10.23 at 10:15
WIAS R406 and online
Quantum Computing for Differential Equations and Surrogate Modeling
Abstract. Quantum computing has transitioned from theoretical promise to practical reality... In this presentation, I will offer an overview of the current state of quantum computing, discuss methodologies for solving differential equations directly on quantum platforms, and explore the use of quantum machine learning to create surrogate models for complex systems.
Tue, 29.08.23 at 14:00
WIAS ESH and online
A proximal trust-region method for nonsmooth optimization with inexact function and gradient evaluations
Abstract. We develop a novel trust-region method to minimize the sum of a smooth nonconvex function and a nonsmooth convex function. ... We demonstrate its efficacy on examples from data science and PDE-constrained optimization.
Thu, 20.07.23 at 14:00
WIAS R406 and online
Uncertainty quantification for models involving hysteresis operators
Abstract. Parameters within models involving hysteresis operators ... These are results of a joined work with Carmine Stefano Clemente and Daniele Davino of the Università degli Studi del Sannio, Benevento, Italy and Ciro Visone of Università di Napoli Federico II, Napoli, Italy.
Mon, 10.07.23 at 14:00
Online
A semismooth Newton solver with automatic differentiation written in C++
Abstract. In this talk we consider problems of the form F(x)=0 where F is a nonlinear Newton differentiable mapping between Sobolev spaces. ... An example implementation is given for a thermoforming model from a recent paper. To verify the solver, the results of this model are reproduced.
Tue, 20.06.23 at 14:00
WIAS ESH and online
Deep Learning with variable time stepping
Abstract. Feature propagation in Deep Neural Networks (DNNs) can be associated to nonlinear discrete dynamical systems. ... The proposed approach is applied to an ill-posed 3D-Maxwell's equation.
Tue, 06.06.23 at 14:00
WIAS HVP5-7 and o...
Physics-informed neural control of partial differential equations with applications to numerical homogenisation
Abstract. In this talk we discuss a model for numerical homogenisation based on the combination of physics-informed neural networks and standard numerical approximation techniques. ... We discuss physics-informed neural networks, the numerical homogenisation modelling framework and related concepts.
Thu, 25.05.23 at 14:00
WIAS ESH and online
Proximal Galerkin: Structure-preserving finite element analysis for free boundary problems, maximum principles, and optimal design
Abstract. One of the longest-standing challenges in finite element analysis is to develop a stable, scalable, high-order Galerkin method that strictly enforces pointwise bound constraints. ... The overall latent variable proximal Galerkin combines ideas from nonlinear programming, functional analysis, tropical algebra, and differential geometry.
Wed, 24.05.23 at 15:15
WIAS ESH (joint w...
Degenerate hysteresis in partially saturated porous media
Abstract. We propose a model for fluid diffusion in partially saturated porous media taking into account hysteresis effects in the pressure-saturation relation. ... This is a joint work with Chiara Gavioli from TU Wien.
Thu, 04.05.23 at 14:00
WIAS ESH and online
Convergence analysis of the nonoverlapping Robin-Robin method for nonlinear elliptic equations
Abstract. The nonoverlapping Robin-Robin method is commonly encountered when discretizing elliptic equations, as it enables the usage of parallel and distributed hardware. ... This framework allows the reformulation of the Robin-Robin method into a Peaceman-Rachford splitting on the interfaces of the subdomains.
Tue, 25.04.23 at 14:00
WIAS HVP5-7 R411 ...
Optimality conditions for problems with probabilistic state constraints
Abstract. In this talk, we discuss optimization problems subject to probabilistic constraints. ... Perspectives for the numerical solution of these problems are discussed, as well as planned research directions.
Wed, 22.03.23 at 10:00
WIAS R406 and online
On the identification and optimization of nonsmooth superposition operators in semilinear elliptic PDEs
Abstract. We study an infinite-dimensional optimization problem that aims to identify the Nemytskii operator in the nonlinear part of a prototypical semilinear elliptic partial differential equation which minimizes the distance between the PDE-solution and a given desired state. ... It is also shown that the established first-order necessary optimality conditions imply that locally optimal superposition operators share various characteristic properties with commonly used activation functions.
Thu, 16.02.23 at 14:00
Online talk and W...
The Hamilton-Jacobi Formulation of Optimal Path Planning for Autonomous Vehicles
Abstract. We present a partial-differential-equation-based optimal path planning framework for simple self-driving cars. ... We demonstrate all of our methods with several examples.
Thu, 26.01.23 at 10:00
WIAS HVP5-7 R411 ...
Machine Learning for Quantitative MRI
Abstract. The field of quantitative Magnetic Resonance Imaging aims at extracting physical tissue parameters from a sequence of highly under sampled MR images. ... Moreover numerical results and open questions are presented.
Mon, 19.12.22 at 15:00
WIAS R406 and online
Deriving a constrained Mean-Field Game
Abstract. Mean-Field Games (MFGs) have a wide area of applications, i.e. crowd motion, flocking models, or behavior of investors. ... In the end, we will discuss some ideas on how to solve such constrained MFGs.
Thu, 10.11.22 at 11:00
WIAS HVP5-7 R411
Analysis of stochastic gradient descent in continuous time
Abstract. Optimisation problems with discrete and continuous data appear in statistical estimation, machine learning, functional data science, robust optimal control, and variational inference. ... In the same setting, we also obtain ergodicity and convergence to the minimiser of the full target function when the learning rate decreases over time sufficiently slowly.
Mon, 11.07.22 at 15:00
WIAS HVP5-7 R411
Some aspects of elliptic quasi-variational inequalities
Abstract. Quasi-variational inequalities (QVIs) can be thought of as generalisations of variational inequalities where the constraint set in which the solution is sought depends on the unknown solution itself. ... and associated stationarity systems.
Wed, 22.06.22 at 14:15
WIAS HVP5-7 R411
Model order reduction techniques for electrical machines
Abstract. In this talk, I will discuss model order reduction methods for parameterized elliptic and parabolic partial differential equations and their application to the modelling of magnetic fields in electrical machines. If time permits, modern deep learning methods of model order reduction will be discussed.
Wed, 08.06.22 at 14:00
WIAS HVP5-7 R411
Dictionary learning for quantitative MRI
Abstract. A nonlinear inverse problem related to quantitative Magnetic Resonance Imaging (qMRI) is under consideration. ... Numerical experiments are performed for two quasi-variational inequalities with application to thermoforming and biomedicine, respectively.
Tue, 31.05.22 at 14:00
WIAS HVP5-7 R411
From N-player games to mean-field games
Abstract. We consider deterministic differential games with a large, but finite, population of symmetric interacting players. The interaction term is of mean-field type and exhibits heterogeneity both via the linear dynamics of the players and in their non-smooth cost functionals. We proceed on a first-step with only constraints on the control and with no additional state constraints. We characterise optimal solutions by deriving first-order optimality conditions. However, due to the non-smoothness of the objectives, set-valued mappings appear in the adjoint equation. To overcome this issue, we make use of a Huber-type regularisation. Furthermore, we aim at analysing the asymptotic behaviour of this system, for infinitely many players. This limiting analysis renders possible the construction of approximate Nash equilibria for the N-player games based on a solution of the corresponding mean-field game.
Fri, 15.04.22
Online
Combined Regularization and Discretization of Equilibrium Problems and Primal-Dual Gap Estimators
Abstract. In this talk, we adress the treatment of finite element discretizations of a class of equilibrium problems involving moving constraints. Therefore, a Moreau-Yosida based regularization technique, controlled by a parameter, is discussed. A generalized Γ-convergence concept is utilized to obtain a priori results. The same technique is applied to the discretization and the combination of both. In addition, a primal-dual gap technique is used for the derivation of error estimators and a strategy for balancing between a refinement of the mesh and an update of the regularization parameter is established. The theoretical findings are illustrated for the obstacle problem as well as numerical experiments are performed for two quasi-variational inequalities with application to thermoforming and biomedicine, respectively.
Sat, 12.03.22 at 13:00
WIAS-R 406
Topics in gas transport: Nash equilibrium and constrained exact boundary controllability
Abstract. We present two results related to the transport of gas: the existence of a solution to a Generalized Nash Equilibrium Problem (GNEP) arising from the modeling of the gas market as an oligopoly, that is only the producers are players, and the consumers just react to the quantity of gas available. In a second part, the constrained exact boundary controllability of a semilinear hyperbolic PDE is investigated. The existence of an absolutely continuous solution and boundary control will be shown, under appropriate assumptions.
Sun, 27.02.22 at 11:00
WIAS ESH
Optimal control of a semilinear heat equation subject to state and control constraints
Abstract. In this talk we consider an optimal control problem governed by a semilinear heat equation with bilinear control-state terms and subject to control and state constraints. The state constraints are of integral type, the integral being with respect to the space variable. The control is multidimensional and the cost functional is of tracking type and contains a linear term in the control variable. We derive second-order necessary and sufficient conditions relying on the concept of alternative costates, quasi-radial critical directions, and the Goh transformation.
Thu, 16.12.21 at 14:00
WIAS ESH
Optimization on low-rank manifolds
Abstract. Low-rank matrix and tensor models are important in many applications for representing and embedding high-dimensional data or functions. They typically lead to non-convex optimization problems on sets of matrices or tensors of given rank. In this talk, we give a basic introduction to the geometry of such sets and how it can be used to derive and study optimization algorithms. Compared to direct optimization of the factors in the model, the geometric approach is more intrinsic and can lead to improved methods. For a class of quadratic cost functions on matrices we also discuss how the geometric viewpoint is useful for studying the non-convex optimization landscape under low-rank constraints.
Sun, 21.11.21
WIAS ESH
On the existence of solutions and solution methods for elliptic obstacle-type quasi-variational inequalities with volume constraints
Abstract. In this talk, an elliptic obstacle-type quasi-variational inequality (QVI) with volume constraints is studied. This type of QVI is motivated by the reformulation of a compliant obstacle problem, where two elastic membranes are subject to external forces while enclosing a constant volume. The existence of solutions to this QVI is established building on fixed-point arguments and partly on the concept of Mosco-convergence. Since Mosco-convergence of the considered feasible sets usually requires complete continuity or compactness properties of the obstacle map, a two-fold approach is explored towards generalising the available existence results for the considered QVI. Based on the analytical findings, the solution of the QVI is approached by solving a sequence of variational inequalities (VIs). Each of these VIs is tackled in function space via a path-following semismooth Newton method. An a posteriori error estimator is derived towards enhancement of the algorithm's numerical performance by using adaptive finite element methods.
Thu, 12.03.20 at 13:00
WIAS R406
Topics in gas transport: Nash equilibrium and constrained exact boundary controllability
Abstract. We present two results related to the transport of gas: the existence of a solution to a Generalized Nash Equilibrium Problem (GNEP) arising from the modeling of the gas market as an oligopoly, that is only the producers are players, and the consumers just react to the quantity of gas available. In a second part, the constrained exact boundary controllability of a semilinear hyperbolic PDE is investigated. The existence of an absolutely continuous solution and boundary control will be shown, under appropriate assumptions.
Thu, 27.02.20 at 11:00
WIAS ESH
Optimal control of a semilinear heat equation subject to state and control constraints
Abstract. In this talk we consider an optimal control problem governed by a semilinear heat equation with bilinear control-state terms and subject to control and state constraints. ... We derive second-order necessary and sufficient conditions relying on the concept of alternative costates, quasi-radial critical directions, and the Goh transformation.
Mon, 16.12.19 at 14:00
WIAS ESH
Optimization on low-rank manifolds
Abstract. Low-rank matrix and tensor models are important in many applications for representing and embedding high-dimensional data or functions. ... For a class of quadratic cost functions on matrices we also discuss how the geometric viewpoint is useful for studying the non-convex optimization landscape under low-rank constraints.
Thu, 21.11.19 at 11:00
WIAS ESH
On the existence of solutions and solution methods for elliptic obstacle-type quasi-variational inequalities with volume constraints
Abstract. In this talk, an elliptic obstacle-type quasi-variational inequality (QVI) with volume constraints is studied. ... An a posteriori error estimator is derived towards enhancement of the algorithm's numerical performance by using adaptive finite element methods.
Fri, 01.11.19 at 14:00
WIAS ESH
Random PDEs on moving hypersurfaces
Abstract. It is well-known that in a variety of applications, especially in the biological modeling, PDEs that appear can be better formulated on evolving curved domains. ... Our theoretical convergence rates are confirmed by numerical experiments. This work is supported by DFG through project AA1-3 of MATH+.
Wed, 23.10.19 at 11:00
WIAS HVP11A R 3.13
A variational model for learning convolutional image atoms from incomplete data
Abstract. Using lifting and relaxation strategies, we present a convex variational model for learning a convolutional sparse representation of image data via a few basic atoms. ... such an atom-based representation is computed from incomplete, noisy and blurry data.
Thu, 26.09.19 at 15:00
WIAS R406
Sensitivity in rate independent evolutions
Abstract. As a topic in science, rate independent evolutions have appeared more than 100 years ago; their study as a mathematical subject in its own began in the 1960's. ... we will present in particular the question of differential sensitivity, that is, whether the associated solution operators possess weak derivatives.
Fri, 02.08.19 at 15:15
WIAS ESH
Efficient optimization algorithms for large scale data analysis
Abstract. In this talk, two classes of problems in large scale data analysis and their optimization algorithms will be discussed. ... Numerical results of applications, e.g., electronic structure calculations, l1-regularized logistic regression problems, Lasso problems and Hartree-Fock total energy minimization problems, will be highlighted.
Wed, 10.07.19 at 13:00
WIAS ESH
Estimation of extreme event probabilities by combining large deviation theory and PDE-constrained optimization, with application to tsunami waves
Abstract. Tsunami waves are caused by a sudden change of ocean depth (bathymetry) after an earthquake below the ocean floor. ... Preliminary numerical results with the 1D inviscid shallow water equation are presented. This is joint work with Shanyin Tong and Eric Vanden-Eijnden (both NYU).
Mon, 03.06.19 at 11:30
WIAS ESH
Quantitative magnetic resonance imaging: From fingerprinting to integrated physics-based models
Abstract. In this talk, we introduce a novel method for quantitative MRI. ... The efficiency of our new method is proved theoretically and also verified by numerical examples.
Mon, 03.06.19 at 11:00
WIAS ESH
Approximate large-scale Bayesian inference with application to magnetic resonance fingerprinting
Abstract. A class of nonlinear, large-scale regression problems is considered where the parameters model the spatial distribution of some property. ... Finally, the approach is applied to MRF. In using simulated data with known ground truth, it is shown that by using the prior knowledge of smoothness in the spatial distribution of the sought parameters, the results are significantly better than those achieved through maximum likelihood estimation.
Wed, 23.01.19 at 13:00
WIAS ESH
On second order optimality conditions for control-affine problems: the finite and infinite dimensional case
Abstract. In this talk I will present the main features of first and second order optimality conditions for optimal control problems of ordinary differential equations that are affine with respect to the control. ... Finally, if time allows it, I will briefly discuss the state-constrained case.
Wed, 16.01.19 at 13:00
WIAS ESH
Optimal control of a coupled Cahn-Hilliard-Navier-Stokes system with variable fluid densities
Abstract. This talk is concerned with the optimal control of two immiscible fluids with non-matched densities. ... The method is based on an adaptation of a bundle-free implicit programming approach for MPECs in function space presented by Hintermüller and Surowiec in 2016.