Network Model
Network models are mathematical representations of interconnected systems, aiming to understand and predict their behavior. Current research focuses on developing sophisticated models using graph neural networks (GNNs), stochastic block models (SBMs), and agent-based approaches, often incorporating techniques like Fisher Information Matrix-based unlearning and deep Gaussian process emulation to improve accuracy and efficiency. These advancements are crucial for diverse applications, including social network analysis, disease modeling, network optimization, and risk prediction, enabling more accurate insights and informed decision-making across various fields.
21papers
Papers
March 24, 2025
January 29, 2025
January 2, 2025
December 5, 2024
November 22, 2024
November 4, 2024
June 4, 2024
March 30, 2024