4 papers
A Jump-Diffusion Framework for Irregular Time Series Generation
O. Pfohl, J. Chemseddine, P. Hagemann +3
We propose a framework for generative modeling of continuous-time processes from irregularly and asynchronously recorded data. It is based on the matching of generators and accommo…
Fast Summation of Radial Kernels via QMC Slicing
Johannes Hertrich, Tim Jahn, Michael Quellmalz
The fast computation of large kernel sums is a challenging task, which arises as a subproblem in any kernel method. We approach the problem by slicing, which relies on random proje…
Early Stopping of Untrained Convolutional Neural Networks
Tim Jahn, Bangti Jin
In recent years, new regularization methods based on (deep) neural networks have shown very promising empirical performance for the numerical solution of ill-posed problems, e.g.,…
Efficient solution of ill-posed integral equations through averaging
Michael Griebel, Tim Jahn
This paper discusses the error and cost aspects of ill-posed integral equations when given discrete noisy point evaluations on a fine grid. Standard solution methods usually employ…