3 citations · 3 across the 9 of their papers we have counts for
4 papers · 1 filter
Dirac-Equation Signal Processing: Physics Boosts Topological Machine Learning
Runyue Wang, Yu Tian, Pietro Liò +1
Topological signals are variables or features associated with both nodes and edges of a network. Recently, in the context of Topological Machine Learning, great attention has been…
Matrix-weighted networks for modeling multidimensional dynamics
Yu Tian, Sadamori Kojaku, Hiroki Sayama +1
Networks are powerful tools for modeling interactions in complex systems. While traditional networks use scalar edge weights, many real-world systems involve multidimensional inter…
Balance with Memory in Signed Networks via Mittag-Leffler Matrix Functions
Yu Tian, Ernesto Estrada
Structural balance is an important characteristic of graphs/networks where edges can be positive or negative, with direct impact on the study of real-world complex systems. When a…
Strong and Weak Random Walks on Signed Networks
Shazia'Ayn Babul, Yu Tian, Renaud Lambiotte
Random walks play an important role in probing the structure of complex networks. On traditional networks, they can be used to extract community structure, understand node centrali…