no code implementations • 23 Feb 2024 • Hubert Wagner, Nickolas Arustamyan, Matthew Wheeler, Peter Bubenik
In particular, we introduce: (1) a mixup barcode, which captures geometric-topological interactions (mixup) between two point sets in arbitrary dimension; (2) simple summary statistics, total mixup and total percentage mixup, which quantify the complexity of the interactions as a single number; (3) a software tool for playing with the above.
no code implementations • 23 Jan 2024 • David Murrugarra, Alan Veliz-Cuba, Elena Dimitrova, Claus Kadelka, Matthew Wheeler, Reinhard Laubenbacher
This paper presents an approach to model-based control that exploits two common features of biological networks, namely their modular structure and canalizing features of their regulatory mechanisms.
no code implementations • 19 Oct 2021 • Matthew Wheeler, Jose Bouza, Peter Bubenik
We use topological data analysis (TDA) to study how data transforms as it passes through successive layers of a deep neural network (DNN).