5 citations · 11 across the 14 of their papers we have counts for
5 papers · 1 filter
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…
Exploring the Enigma of Neural Dynamics Through A Scattering-Transform Mixer Landscape for Riemannian Manifold
Tingting Dan, Ziquan Wei, Won Hwa Kim +1
The human brain is a complex inter-wired system that emerges spontaneous functional fluctuations. In spite of tremendous success in the experimental neuroscience field, a system-le…
Message Detouring: A Simple Yet Effective Cycle Representation for Expressive Graph Learning
Ziquan Wei, Tingting Dan, Guorong Wu
Graph learning is crucial in the fields of bioinformatics, social networks, and chemicals. Although high-order graphlets, such as cycles, are critical to achieving an informative g…
Learning to Approximate Adaptive Kernel Convolution on Graphs
Jaeyoon Sim, Sooyeon Jeon, InJun Choi +2
Various Graph Neural Networks (GNNs) have been successful in analyzing data in non-Euclidean spaces, however, they have limitations such as oversmoothing, i.e., information becomes…