3 citations · 3 across the 9 of their papers we have counts for
9 papers
Ollivier's Ricci Curvature on Complex-weighted Graphs
Yu Tian, Eleanor Wiesler, Melanie Weber
Understanding the geometry of complex networks is critical for effective modeling and analysis across domains. While discrete notions of Ricci curvature have emerged as powerful to…
GEMINI: Generalized Ensnarlment Measure from Incomplete-linkage of Network-network Interactions
Yu Tian, Chinmayi Subramanya, Carl D. Modes
Spatially embedded networks are central to many physical and biological systems, where geometry and connectivity jointly shape structure and function. Examples abound across the sc…
Complex-Weighted Convolutional Networks: Provable Expressiveness via Complex Diffusion
Cristina López Amado, Tassilo Schwarz, Yu Tian +1
Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications, yet they remain limited by oversmoothing and poor performance on heterophilic graphs. To…
Global Synchronization in Matrix-Weighted Networks
Anna Gallo, Yu Tian, Renaud Lambiotte +1
Synchronization phenomena in complex systems are fundamental to understanding collective behavior across disciplines. While classical approaches model such systems by using scalar-…
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…
Percolation Theories for Quantum Networks
Xiangyi Meng, Xinqi Hu, Yu Tian +4
Quantum networks have experienced rapid advancements in both theoretical and experimental domains over the last decade, making it increasingly important to understand their large-s…