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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Zhen-Qiao Liu

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Open access 2026

GPC-CF: A Graph Convolutional Pre-Trained Contrastive Cross-Fusion Framework for Multimodal Brain Representation Learning

A novel Graph Convolutional Pre-trained Contrastive Cross-Fusion (GPC-CF) framework, which integrates EEG and fMRI data within a pre-training and fine-tuning model to establish a powerful paradigm for multimodal brain signal fusion.

Rui-Zhe Zhong, Hai-Sheng Li, Min Zuo et al. · 0 citations
Oct 2026

Multi-Dimensional Feature Adaptive Gating Network for Multi-View and Whole-Brain Magnetic Resonance Imaging-Based Alzheimer's Disease Classification.

A reproducible and explainable deep learning framework, termed the multidimensional feature adaptive gating network (MDFAG-Net), for sMRI-based AD classification and neuroimaging analysis, which demonstrated competitive classification performance and outperformed representative two-dimensional, three-dimensional, and m...

Yi-Peng Zhou, Lin Zhu, Zhen-Qiao Liu et al. · 0 citations
Jul 2026

Multi-Scale Structural MRI Features Reveal Task-Based Functional Connectivity and Its Alterations in Psychiatric Disorders: A Collaborative Graph Attention Network Approach

The Collaborative Graph Attention Multi-Task Network (CoGA-MTN), a deep learning framework that integrates multi-scale structural features to jointly predict task-based functional connectivity (FC) and identify potential disease-related network alterations, is introduced.

Qingchuan Zhang, Zhen-Qiao Liu, Wen-Jie Dou et al. · 0 citations
Open access Jul 2026

TF-JointMAE: a self-supervised multi-representation EEG learning framework for Alzheimer’s disease spectrum classification

A self-supervised masked autoencoder pre-training on multiple public EEG datasets demonstrates that TF-JointMAE effectively improves the robustness of EEG representations, providing potential auxiliary support for AD-spectrum classification and clinical decision-making.

Min Zuo, Hong Zhu, Zhen-Qiao Liu et al. · 0 citations

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