6 citations · 24 across the 21 of their papers we have counts for
5 papers · 1 filter
Faster Inference of Cell Complexes from Flows via Matrix Factorization
Til Spreuer, Josef Hoppe, Michael T. Schaub
We consider the following inference problem: Given a set of edge-flow signals observed on a graph, lift the graph to a cell complex, such that the observed edge-flow signals can be…
Global Ground Metric Learning with Applications to scRNA data
Damin Kühn, Michael T. Schaub
Optimal transport provides a robust framework for comparing probability distributions. Its effectiveness is significantly influenced by the choice of the underlying ground metric.…
Don't be Afraid of Cell Complexes! An Introduction from an Applied Perspective
Josef Hoppe, Vincent P. Grande, Michael T. Schaub
Cell complexes (CCs) are a higher-order network model deeply rooted in algebraic topology that has gained interest in signal processing and network science recently. The processing…
HLSAD: Hodge Laplacian-based Simplicial Anomaly Detection
Florian Frantzen, Michael T. Schaub
In this paper, we propose HLSAD, a novel method for detecting anomalies in time-evolving simplicial complexes. While traditional graph anomaly detection techniques have been extens…
A Bayesian Perspective on Uncertainty Quantification for Estimated Graph Signals
Lennard Rompelberg, Michael T. Schaub
We present a Bayesian perspective on quantifying the uncertainty of graph signals estimated or reconstructed from imperfect observations. We show that many conventional methods of…