IEEE

PBGMR: A Physics-Informed Bayesian Graph Neural Network for Robust Multimodal Underwater ...

Abstract: Existing approaches for underwater autonomous target recognition (UATR) often suffer from limited accuracy and robustness due to complex underwater environments, noise interference during ...
Devdiscourse

AI’s growing role in cancer, rare disease and COVID-19 drug repurposing

For rare diseases, AI-driven repurposing fills a critical gap. With more than 7000 rare diseases and only a small percentage ...

Xiaofei Han Publishes Groundbreaking Research on Multimodal Graph Neural Networks in ...

Frontiers in Neurorobotics has published a new paper by Xiaofei Han and Xin Dou introducing a next-generation artificial intelligence framework that combines graph neural networks and multimodal ...
IEEE

Finite-Size Convergence Bound of Graph Convolutional Networks by Graphon Analysis

Abstract: Graph Convolutional Networks (GCNs) prevail in the analysis of network-structured data, but how the graph size affects the performance is not fully understood. As the limit of graphs, the ...