2024-2027 Grants-in-Aid for Scientific Research (KAKENHI) Grant-in-Aid for Challenging Exploratory Research, JSPS

The collective dynamics of complex networks found in matter, life, and society often go beyond what can be explained by individual components and their pairwise relationships, showing emergent behavior governed by higher-order interactions. However, due to the lack of a concise modeling framework for higher-order interactions in complex networks, their roles and functions in collective dynamics remain unclear. This study aims to develop mathematical modeling techniques to describe and analyze complex networks with higher-order interactions, focusing on neural networks on curved statistical manifolds based on Renyi divergence, with the goal of significantly transforming the current modeling framework of complex networks.