In this work, we explore the influence of entropy change in deep learnin...
With the popularity of deep neural networks (DNNs), model interpretabili...
Artificial General Intelligence (AGI) is poised to revolutionize a varie...
Designing more efficient, reliable, and explainable neural network
archi...
The evolution of convolutional neural networks (CNNs) can be largely
att...
Visual attention is a fundamental mechanism in the human brain, and it
i...
Artificial neural networks (ANNs), originally inspired by biological neu...
Shortcut learning is common but harmful to deep learning models, leading...
Learning harmful shortcuts such as spurious correlations and biases prev...
Learning with little data is challenging but often inevitable in various...
Vision transformer (ViT) and its variants have achieved remarkable succe...
Using deep learning models to recognize functional brain networks (FBNs)...
How to identify and characterize functional brain networks (BN) is
funda...
For decades, a variety of predictive approaches have been proposed and
e...
Large-scale collaborative analysis of brain imaging data, in psychiatry ...
Genome-wide association studies (GWAS) have achieved great success in th...