3 papers
cs.CV2025
Challenges in 3D Data Synthesis for Training Neural Networks on Topological Features
Dylan Peek, Matthew P. Skerritt, Siddharth Pritam +1
Topological Data Analysis (TDA) involves techniques of analyzing the underlying structure and connectivity of data. However, traditional methods like persistent homology can be com…
cs.CV2025
Noise-Robust Topology Estimation of 2D Image Data via Neural Networks and Persistent Homology
Dylan Peek, Matthew P. Skerritt, Stephan Chalup
Persistent Homology (PH) and Artificial Neural Networks (ANNs) offer contrasting approaches to inferring topological structure from data. In this study, we examine the noise robust…
q-bio.NC2025
Time Series Analysis of Spiking Neural Systems via Transfer Entropy and Directed Persistent Homology
Dylan Peek, Siddharth Pritam, Matthew P. Skerritt +1
We present a topological framework for analysing neural time series that integrates Transfer Entropy (TE) with directed Persistent Homology (PH) to characterize information flow in…