BrainATCL: Adaptive Temporal Brain Connectivity Learning for Functional Link Prediction and Age Estimation
cs.LG
Submitted: 2025-08-09
Updated: 2025-08-09
Journal ref: Proceedings of The 9th International Conference on Medical Imaging with Deep Learning, PMLR 315:3947-3970, 2026
Code: https://github.com/neuro-researcher123/dynamic-fc
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Deep Gaussian Embedding of Graphs: Unsupervised Inductive Learning via Ranking
- Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
- Mamba: Linear-Time Sequence Modeling with Selective State Spaces
- Efficiently Modeling Long Sequences with Structured State Spaces
- Strategies for Pre-training Graph Neural Networks
- Brain Network Transformer
- Semi-Supervised Classification with Graph Convolutional Networks
- A Comparative Study on Dynamic Graph Embedding based on Mamba and Transformers
- Graph Attention Networks
- STNAGNN: Data-driven Spatio-temporal Brain Connectivity beyond FC
- How Powerful are Graph Neural Networks?
- DynSTG-Mamba: Dynamic Spatio-Temporal Graph Mamba with Cross-Graph Knowledge Distillation for Gait Disorders Recognition
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