2 citations · 5 across the 6 of their papers we have counts for
6 papers
Dynamical Measure Transport and Neural PDE Solvers for Sampling
Jingtong Sun, Julius Berner, Lorenz Richter +4
The task of sampling from a probability density can be approached as transporting a tractable density function to the target, known as dynamical measure transport. In this work, we…
Gauss-Newton Natural Gradient Descent for Physics-Informed Computational Fluid Dynamics
Anas Jnini, Flavio Vella, Marius Zeinhofer
We propose Gauss-Newton's method in function space for the solution of the Navier-Stokes equations in the physics-informed neural network (PINN) framework. Upon discretization, thi…
The modelling error in multi-dimensional time-dependent solute transport models
Rami Masri, Marius Zeinhofer, Miroslav Kuchta +1
Starting from full-dimensional models of solute transport, we derive and analyze multi-dimensional models of time-dependent convection, diffusion, and exchange in and around pulsat…
The Deep Ritz Method for Parametric -Dirichlet Problems
Alex Kaltenbach, Marius Zeinhofer
We establish error estimates for the approximation of parametric -Dirichlet problems deploying the Deep Ritz Method. Parametric dependencies include, e.g., varying geometries an…
Three Dimensional Optimization of Scaffold Porosities for Bone Tissue Engineering
Patrick Dondl, Marius Zeinhofer
We consider the scaffold design optimization problem associated to the three dimensional, time dependent model for scaffold mediated bone regeneration considered in Dondl et al. (2…
Regularity for Reaction-Diffusion Equations with Non-smooth Data
Patrick Dondl, Marius Zeinhofer
We prove an regularity result for a reaction-diffusion equation with mixed boundary conditions, symmetric coefficients and an initial conditio…