5 papers
Graph-theoretic design of lasing networks for physical vision
Paul Obernolte, Jakub Dranczewski, Yixiu Yin +10
Physical neural networks perform learning through the intrinsic nonlinear dynamics of matter. Optimising their design presents a considerable challenge: complex many-body physics c…
Information-theoretic signatures of causality in Bayesian networks and hypergraphs
Sung En Chiang, Zhaolu Liu, Robert L. Peach +1
Analyzing causality in multivariate systems involves establishing how information is generated, distributed and combined. Traditional causal discovery frameworks are capable of mul…
PyGenStability: Multiscale community detection with generalized Markov Stability
Alexis Arnaudon, Juni Schindler, Robert L. Peach +4
We present PyGenStability, a general-use Python software package that provides a suite of analysis and visualisation tools for unsupervised multiscale community detection in graphs…
Permutation-Free High-Order Interaction Tests
Zhaolu Liu, Robert L. Peach, Mauricio Barahona
Kernel-based hypothesis tests offer a flexible, non-parametric tool to detect high-order interactions in multivariate data, beyond pairwise relationships. Yet the scalability of su…
Information-Theoretic Measures on Lattices for High-Order Interactions
Zhaolu Liu, Mauricio Barahona, Robert L. Peach
Traditional measures based solely on pairwise associations often fail to capture the complex statistical structure of multivariate data. Existing approaches for identifying informa…