3 citations · 4 across the 7 of their papers we have counts for
8 papers
SPACE: Source-free Proxy Anchor Concept Erasure for MLLMs
Zhijing Zhang, Jiaqi Ding, Qianshan Wei +5
As Multimodal Large Language Models (MLLMs) face growing privacy risks and regulatory constraints, machine unlearning (MU) has emerged as a crucial solution for removing sensitive…
Matrix-Response Generalized Linear Mixed Model with Applications to Longitudinal Brain Images
Zhentao Yu, Jiaqi Ding, Guorong Wu +1
Longitudinal brain imaging data facilitate the monitoring of structural and functional alterations in individual brains across time, offering essential understanding of dynamic neu…
GeoDynamics: A Geometric State-Space Neural Network for Understanding Brain Dynamics on Riemannian Manifolds
Tingting Dan, Jiaqi Ding, Guorong Wu
State-space models (SSMs) have become a cornerstone for unraveling brain dynamics, revealing how latent neural states evolve over time and give rise to observed signals. By combini…
Explore Brain-Inspired Machine Intelligence for Connecting Dots on Graphs Through Holographic Blueprint of Oscillatory Synchronization
Tingting Dan, Jiaqi Ding, Guorong Wu
Neural coupling in both neuroscience and artificial intelligence emerges as dynamic oscillatory patterns that encode abstract concepts. To this end, we hypothesize that a deeper un…
Understanding Mechanistic Role of Structural and Functional Connectivity in Tau Propagation Through Multi-Layer Modeling
Tingting Dan, Xinwei Huang, Jiaqi Ding +2
Emerging neuroimaging evidence shows that pathological tau proteins build up along specific brain networks, suggesting that large-scale network architecture plays a key role in the…
BrainMAP: Learning Multiple Activation Pathways in Brain Networks
Song Wang, Zhenyu Lei, Zhen Tan +8
Functional Magnetic Resonance Image (fMRI) is commonly employed to study human brain activity, since it offers insight into the relationship between functional fluctuations and hum…
NeuroPath: A Neural Pathway Transformer for Joining the Dots of Human Connectomes
Ziquan Wei, Tingting Dan, Jiaqi Ding +1
Although modern imaging technologies allow us to study connectivity between two distinct brain regions in-vivo, an in-depth understanding of how anatomical structure supports brain…
Machine Learning on Dynamic Functional Connectivity: Promise, Pitfalls, and Interpretations
Jiaqi Ding, Tingting Dan, Ziquan Wei +4
An unprecedented amount of existing functional Magnetic Resonance Imaging (fMRI) data provides a new opportunity to understand the relationship between functional fluctuation and h…