Zening Fu

Orcid: 0000-0002-1591-4900

According to our database1, Zening Fu authored at least 67 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Maximum Classifier Discrepancy Generative Adversarial Network for Jointly Harmonizing Scanner Effects and Improving Reproducibility of Downstream Tasks.
IEEE Trans. Biomed. Eng., April, 2024

Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer's Disease and Cognitive Impairment.
Sensors, February, 2024

Multiscale Neuroimaging Features for the Identification of Medication Class and Non-Responders in Mood Disorder Treatment.
CoRR, 2024

A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age.
Brain Connect., 2024

2023
Disrupted Dynamic Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease.
Brain Connect., August, 2023

Capturing Spatial Dynamics Using Time-Resolved Referenced-Informed Network Estimation Techniques.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

MultiViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023

Self-Supervised Mental Disorder Classifiers via Time Reversal.
Proceedings of the International Joint Conference on Neural Networks, 2023

Glacier: Glass-Box Transformer for Interpretable Dynamic Neuroimaging.
Proceedings of the IEEE International Conference on Acoustics, 2023

Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data.
Proceedings of the IEEE International Conference on Acoustics, 2023

Phase and amplitude, two sides of functional connectivity.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

Functional and Structural Longitudinal Change Patterns in Adolescent Brain.
Proceedings of the 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2023

Multimodal Fusion of Functional and Structural Data to Recognize Longitudinal Change Patterns in the Adolescent Brain.
Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2023

2022
Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study.
Neuroinformatics, 2022

Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI.
NeuroImage, 2022

Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping.
NeuroImage, 2022

An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data.
Medical Image Anal., 2022

An Approach to Automatically Label and Order Brain Activity/Component Maps.
Brain Connect., 2022

Multimodel Order Independent Component Analysis: A Data-Driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial Scales.
Brain Connect., 2022

Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics Data.
Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Longitudinal Whole-Brain Functional Network Change Patterns Over A Two-Year Period In The ABCD Data.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022

Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series.
Proceedings of the International Joint Conference on Neural Networks, 2022

'Harmless' adversarial network harmonization approach for removing site effects and improving reproducibility in neuroimaging studies.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Mind the gap: functional network connectivity interpolation between schizophrenia patients and controls using a variational autoencoder.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Functional Connectivity Stability: A Signature of Neurocognitive Development and Psychiatric Problems in Children.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD Study.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

Learning Active Multimodal Subspaces in the Brain.
Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction.
Proceedings of the 22nd IEEE International Conference on Bioinformatics and Bioengineering, 2022

2021
Dynamic state with covarying brain activity-connectivity: On the pathophysiology of schizophrenia.
NeuroImage, 2021

Accessing dynamic functional connectivity using l0-regularized sparse-smooth inverse covariance estimation from fMRI.
Neurocomputing, 2021

Multi network InfoMax: A pre-training method involving graph convolutional networks.
CoRR, 2021

Brain dynamics via Cumulative Auto-Regressive Self-Attention.
CoRR, 2021

Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder.
Brain Connect., 2021

The Influence of Cerebral Small Vessel Disease on Static and Dynamic Functional Network Connectivity in Subjects Along Alzheimer's Disease Continuum.
Brain Connect., 2021

A Deep Learning Model for Data-Driven Discovery of Functional Connectivity.
Algorithms, 2021

A Multimodal Learning Framework to Study Varying Information Complexity in Structural and Functional Sub-Domains in Schizophrenia.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021

Multimodal Brain Age Prediction with Feature Selection and Comparison.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Fusing multimodal neuroimaging data with a variational autoencoder.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021

Machine Learning Predicts Treatment Response in Bipolar & Major Depression Disorders.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

Stability of functional network connectivity (FNC) values across multiple spatial normalization pipelines in spatially constrained independent component analysis.
Proceedings of the 21st IEEE International Conference on Bioinformatics and Bioengineering, 2021

2020
Task-induced brain connectivity promotes the detection of individual differences in brain-behavior relationships.
NeuroImage, 2020

A Machine Learning Model for Exploring Aberrant Functional Network Connectivity Transition in Schizophrenia.
Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation, 2020

Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020

Functional Multi-Connectivity: A Novel Approach To Assess Multi-Way Entanglement Between Networks and Voxels.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020

Aberrant Functional Network Connectivity Transition Probability in Major Depressive Disorder.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

Time-varying Graphs: A Method to Identify Abnormal Integration and Disconnection in Functional Brain Connectivity with Application to Schizophrenia.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

Varying Information Complexity in Functional Domain Interactions in Schizophrenia.
Proceedings of the 20th IEEE International Conference on Bioinformatics and Bioengineering, 2020

2019
Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism.
NeuroImage, 2019

A robust swarm intelligence-based feature selection model for neuro-fuzzy recognition of mild cognitive impairment from resting-state fMRI.
Inf. Sci., 2019

Learnt dynamics generalizes across tasks, datasets, and populations.
CoRR, 2019

Transfer Learning of fMRI Dynamics.
CoRR, 2019

Multimodal Neuroimaging Patterns Associated with Social Responsiveness Impairment in Autism: A Replication Study.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019

Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019

Prediction of Progression to Alzheimer's disease with Deep InfoMax.
Proceedings of the 2019 IEEE EMBS International Conference on Biomedical & Health Informatics, 2019

2018
Connectome-based individualized prediction of temperament trait scores.
NeuroImage, 2018

Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia.
NeuroImage, 2018

Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis.
NeuroImage, 2018

A novel and effective fMRI decoding approach based on sliced inverse regression and its application to pain prediction.
Neurocomputing, 2018

2017
A least across-segment variance (LASV) method for the correction of EEG-fMRI desynchronization.
Proceedings of the 8th International IEEE/EMBS Conference on Neural Engineering, 2017

2015
Supervised nonlinear dimension reduction of functional magnetic resonance imaging data using Sliced Inverse Regression.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

Joint source separation of simultaneous EEG-fMRI recording in two experimental conditions using common spatial patterns.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

L0-regularized time-varying sparse inverse covariance estimation for tracking dynamic fMRI brain networks.
Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2015

2014
Adaptive Covariance Estimation of Non-Stationary Processes and its Application to Infer Dynamic Connectivity From fMRI.
IEEE Trans. Biomed. Circuits Syst., 2014

2013
Estimation of time-varying autocorrelation and its application to time-frequency analysis of nonstationary signals.
Proceedings of the 2013 IEEE International Symposium on Circuits and Systems (ISCAS2013), 2013

Time-varying correlation coefficients estimation and its application to dynamic connectivity analysis of fMRI.
Proceedings of the 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2013

Adaptive window selection in estimating dynamic functional connectivity of resting-state fMRI.
Proceedings of the 9th International Conference on Information, 2013


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