56 citations · 71 across the 3 of their papers we have counts for
4 papers · 1 filter
Interpretable Neural Networks with Random Constructive Algorithm
Jing Nan, Wei Dai
This paper introduces an Interpretable Neural Network (INN) incorporating spatial information to tackle the opaque parameterization process of random weighted neural networks. The…
Transformer-Based Hierarchical Clustering for Brain Network Analysis
Wei Dai, Hejie Cui, Xuan Kan +3
Brain networks, graphical models such as those constructed from MRI, have been widely used in pathological prediction and analysis of brain functions. Within the complex brain syst…
Brain Network Transformer
Xuan Kan, Wei Dai, Hejie Cui +3
Human brains are commonly modeled as networks of Regions of Interest (ROIs) and their connections for the understanding of brain functions and mental disorders. Recently, Transform…
BrainNNExplainer: An Interpretable Graph Neural Network Framework for Brain Network based Disease Analysis
Hejie Cui, Wei Dai, Yanqiao Zhu +3
Interpretable brain network models for disease prediction are of great value for the advancement of neuroscience. GNNs are promising to model complicated network data, but they are…