Wenxing Hu

most citedInterpretable multimodal fusion networks reveal mechanisms of brain cognition

8 citations · 10 across the 3 of their papers we have counts for

collaborators

3 papers

q-bio.NC2020★ 2 cited

Functional connectome fingerprinting: Identifying individuals and predicting cognitive function via deep learning

Biao Cai, Gemeng Zhang, Aiying Zhang +6

The dynamic characteristics of functional network connectivity have been widely acknowledged and studied. Both shared and unique information has been shown to be present in the con…

stat.ML2020

Causal inference of brain connectivity from fMRI with $ψ$ -Learning Incorporated Linear non-Gaussian Acyclic Model ( $ψ$ -LiNGAM)

Aiying Zhang, Gemeng Zhang, Biao Cai +6

Functional connectivity (FC) has become a primary means of understanding brain functions by identifying brain network interactions and, ultimately, how those interactions produce c…

q-bio.NC2020★ 8 cited

Interpretable multimodal fusion networks reveal mechanisms of brain cognition

Wenxing Hu, Xianghe Meng, Yuntong Bai +7

Multimodal fusion benefits disease diagnosis by providing a more comprehensive perspective. Developing algorithms is challenging due to data heterogeneity and the complex within- a…

Functional connectome fingerprinting: Identifying individuals and predicting cognitive function via deep learning

Causal inference of brain connectivity from fMRI with ψ-Learning Incorporated Linear non-Gaussian Acyclic Model (ψ-LiNGAM)

Interpretable multimodal fusion networks reveal mechanisms of brain cognition

Causal inference of brain connectivity from fMRI with $ψ$ -Learning Incorporated Linear non-Gaussian Acyclic Model ( $ψ$ -LiNGAM)