35 citations · 180 across the 39 of their papers we have counts for
7 papers · 1 filter
Learning in High-Dimensional Feature Spaces Using ANOVA-Based Fast Matrix-Vector Multiplication
Franziska Nestler, Martin Stoll, Theresa Wagner
Kernel matrices are crucial in many learning tasks such as support vector machines or kernel ridge regression. The kernel matrix is typically dense and large-scale. Depending on th…
An Improved Penalty Algorithm using Model Order Reduction for MIPDECO problems with partial observations
Dominik Garmatter, Margherita Porcelli, Francesco Rinaldi +1
This work addresses optimal control problems governed by a linear time-dependent partial differential equation (PDE) as well as integer constraints on the control. Moreover, partia…
RaWaNet: Enriching Graph Neural Network Input via Random Walks on Graphs
Anahita Iravanizad, Edgar Ivan Sanchez Medina, Martin Stoll
In recent years, graph neural networks (GNNs) have gained increasing popularity and have shown very promising results for data that are represented by graphs. The majority of GNN a…
A low-rank tensor method to reconstruct sparse initial states for PDEs with Isogeometric Analysis
Alexandra Bünger, Martin Stoll
When working with PDEs the reconstruction of a previous state often proves difficult. Good prior knowledge and fast computational methods are crucial to build a working reconstruct…
Orientations and matrix function-based centralities in multiplex network analysis of urban public transport
Kai Bergermann, Martin Stoll
We study urban public transport systems by means of multiplex networks in which stops are represented as nodes and each line is represented by a layer. We determine and visualize p…
Fast computation of matrix function-based centrality measures for layer-coupled multiplex networks
Kai Bergermann, Martin Stoll
Centrality measures identify and rank the most influential entities of complex networks. In this paper, we generalize matrix function-based centrality measures, which have been stu…