Li Shen

A new approach aims to classify Alzheimer's disease using multiple data types.

A new framework enhances learning from pre-trained models without original data.

Exploring Task Groupings Regularization to manage model heterogeneity.

Research introduces a framework to improve understanding of brain networks and connectivity.

A new framework boosts model performance with limited data.

A new method to enhance pre-trained models using selective fine-tuning.

Researchers combine fMRI and MEG to study brain activity during cognitive tasks.

This article explores the behavior and transport of surfactants using computer simulations.

Explore federated learning's approach to privacy in machine learning.

A new model improves AI's ability to learn without forgetting.

A new method improves code output quality from language models.

This article addresses bias in graphical models and proposes a method for fair analysis.

A-FedPD aligns model updates to reduce training instability in federated learning.

A new method improves medical image segmentation using fewer labeled samples.

A look at how graph learning enhances semi-supervised domain adaptation.

FWA improves machine learning speed and generalization through careful weight averaging.

A look at bi-level optimization methods and their impact on machine learning models.

Discover how brain connectomics enhances echo state networks for better predictions.