Abstract: The analysis of complex networks is a rapidly growing field with applications in many diverse areas. A typical computational paradigm is to reduce the system to a set of pairwise relationships modeled by a graph (matrix) and employ tools within this framework. However, many real-world networks feature temporally evolving structures and higher-order interactions. Such components are often missed when using static and lower-order methods. This minisymposium explores recent advances in models, theory, and algorithms for dynamic and higher-order interactions and data, spanning a broad range of topics including persistent homology, tensor analysis, random walks with memory, and higher-order network analysis.
Group1 – Community detection and clustering
Christine Klymko, LLNL
Improving seed set expansion with semi-supervised information
Tim La Fond, LLNL
Representing the Evolution of Communities in Dynamic Networks
Nate Veldt, Purdue
Algorithmic Advances in Higher-Order Correlation Clustering
Marya Bazzi, ATI
Community structure in temporal multilayer networks
Group2 – Simplicial complexes
Heather Harrington, Oxford
Topological data analysis for investigation of dynamics and biological networks
Alice Patania, Indiana
Null hypothesis for simplicial complexes
Braxton Osting, Utah
Spectral Sparsification of Simplicial Complexes for Clustering and Label Propagation
Austin Benson, Cornell
Simplicial closure and higher-order link prediction.
Group3 – Tensor methods and high-performance computing
Francesca Arrigo
Eigenvector-based Centrality Measures in Multilayer Networks
Orly Alter, Utah
Multi-Tensor Decompositions for Personalized Cancer Diagnostics, Prognostics, and Therapeutics.
Chunxing Yin, GA Tech
A New Algorithm Model for Massive-Scale Streaming Graph Analysis
Tahsin Reza, UBC
Distributed Algorithms for Exact and Fuzzy Graph Pattern Matching
Group4 – Higher-order random walks
Eisha Nathan, LLNL
Nonbacktracking Walks in Dynamic Graphs
Michael Schaub, MIT
Random walks on simplicial complexes and the normalized Hodge Laplacian
Keita Iwabuchi, LLNL
Francesco Tudisco, Strathclyde
Higher-order ergodicity coefficients
This event is part of the research project MAGNET for which I would like to acknowledge support from the Marie Curie individual fellowship scheme.