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Zening Fu
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2020 – today
- 2024
- [j25]Rekha Saha
, Debbrata K. Saha
A Method to Estimate Longitudinal Change Patterns in Functional Network Connectivity of the Developing Brain Relevant to Psychiatric Problems, Cognition, and Age. Brain Connect. 14(2): 130-140 (2024) - [j24]Zening Fu
Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. NeuroImage 292: 120617 (2024) - [j23]Pavel Popov
A simple but tough-to-beat baseline for fMRI time-series classification. NeuroImage 303: 120909 (2024) - [j22]Sahithi Kolla, Haleh Falakshahi, Anees Abrol, Zening Fu, Vince D. Calhoun
Intra-Atlas Node Size Effects on Graph Metrics in fMRI Data: Implications for Alzheimer's Disease and Cognitive Impairment. Sensors 24(3): 814 (2024) - [j21]Weizheng Yan
Maximum Classifier Discrepancy Generative Adversarial Network for Jointly Harmonizing Scanner Effects and Improving Reproducibility of Downstream Tasks. IEEE Trans. Biomed. Eng. 71(4): 1170-1178 (2024) - [c47]Md Abdur Rahaman, Zening Fu, Armin Iraji, Vince D. Calhoun:
A Deep Biclustering Framework for Brain Network Analysis. CVPR Workshops 2024: 5075-5085 - [c46]Prerana Bajracharya, Ashkan Faghiri, Zening Fu, Vince D. Calhoun, Sarah Shultz, Armin Iraji:
Identifying Canonical multi-scale Intrinsic Connectivity Networks in Infant resting-state fMRI and their Association with Age. EMBC 2024: 1-4 - [c45]Cyrus Eierud, Zening Fu, Helen Petropoulos, Anastasia Bohsali, Armin Iraji, Melanie Ganz, Cyril R. Pernet, Vince D. Calhoun:
NeuroMark PET: Replicable positron emission tomography ICA templates for florbetapir and florbetaben radioligands. EMBC 2024: 1-4 - [c44]Md Abdur Rahaman, Zening Fu, Armin Iraji, Vince D. Calhoun:
SpaDE: Semantic Locality Preserving Biclustering for Neuroimaging Data. EMBC 2024: 1-5 - [c43]Bradley T. Baker, Mustafa S. Salman, Zening Fu, Armin Iraji, Elizabeth A. Osuch, Henry Jeremy Bockholt, Vince D. Calhoun:
Multiscale Neuroimaging Features for the Identification of Medication Class and Non-Responders in Mood Disorder Treatment. ISBI 2024: 1-5 - [c42]Bhaskar Ray, Jiayu Chen, Zening Fu, Pranav Suresh, Bishal Thapaliya, Britny Farahdel, Vince D. Calhoun, Jingyu Liu:
Replication and Refinement of Brain Age Model for Adolescent Development. ISBI 2024: 1-5 - [c41]Sir-Lord Wiafe, Ashkan Faghiri, Zening Fu, Robyn L. Miller, Vince D. Calhoun:
Capturing Stretching and Shrinking of Inter-Network Temporal Coupling in FMRI Via WARP Elasticity. ISBI 2024: 1-4 - [c40]Sohei Wakisaka
Transformed Skin: Changing own skin texture feeling for VR avatar embodiment. SIGGRAPH Asia Emerging Technologies 2024: 17:1-17:2 - [i13]Bradley T. Baker, Mustafa S. Salman, Zening Fu, Armin Iraji, Elizabeth A. Osuch, Henry Jeremy Bockholt, Vince D. Calhoun:
Multiscale Neuroimaging Features for the Identification of Medication Class and Non-Responders in Mood Disorder Treatment. CoRR abs/2402.07858 (2024) - [i12]Ziyu Zhou, Anton Orlichenko, Gang Qu, Zening Fu, Vince D. Calhoun, Zhengming Ding, Yu-Ping Wang:
An Interpretable Cross-Attentive Multi-modal MRI Fusion Framework for Schizophrenia Diagnosis. CoRR abs/2404.00144 (2024) - [i11]Giorgio Dolci, Federica Cruciani, Md Abdur Rahaman, Anees Abrol, Jiayu Chen, Zening Fu, Ilaria Boscolo Galazzo, Gloria Menegaz, Vince D. Calhoun:
An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease. CoRR abs/2406.13292 (2024) - 2023
- [j20]Mohammad S. Eslampanah Sendi
Disrupted Dynamic Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease. Brain Connect. 13(6): 334-343 (2023) - [c39]Rekha Saha, Debbrata K. Saha, Zening Fu, Rogers F. Silva, Vince D. Calhoun
Multimodal Fusion of Functional and Structural Data to Recognize Longitudinal Change Patterns in the Adolescent Brain. BHI 2023: 1-5 - [c38]Rekha Saha, Debbrata K. Saha, Zening Fu, Rogers F. Silva, Vince D. Calhoun
Functional and Structural Longitudinal Change Patterns in Adolescent Brain. EMBC 2023: 1-4 - [c37]Sir-Lord Wiafe, Zening Fu, Vince D. Calhoun
Phase and amplitude, two sides of functional connectivity. EMBC 2023: 1-4 - [c36]Giorgio Dolci
Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data. ICASSP Workshops 2023: 1-5 - [c35]Usman Mahmood, Zening Fu, Vince D. Calhoun
Glacier: Glass-Box Transformer for Interpretable Dynamic Neuroimaging. ICASSP 2023: 1-5 - [c34]Zafar Iqbal, Usman Mahmood, Zening Fu, Sergey M. Plis:
Self-Supervised Mental Disorder Classifiers via Time Reversal. IJCNN 2023: 1-7 - [c33]Yuda Bi, Anees Abrol, Zening Fu, Vince D. Calhoun
MultiViT: Multimodal Vision Transformer for Schizophrenia Prediction using Structural MRI and Functional Network Connectivity Data. ISBI 2023: 1-5 - [c32]Armin Iraji, Jiayu Chen, Ashkan Faghiri, Zening Fu, Jingyu Liu, Juan R. Bustillo, Tülay Adali, Mukesh Dhamala, Vince D. Calhoun
Capturing Spatial Dynamics Using Time-Resolved Referenced-Informed Network Estimation Techniques. ISBI 2023: 1-4 - 2022
- [j19]Mustafa S. Salman
An Approach to Automatically Label and Order Brain Activity/Component Maps. Brain Connect. 12(1): 85-95 (2022) - [j18]Xing Meng
Multimodel Order Independent Component Analysis: A Data-Driven Method for Evaluating Brain Functional Network Connectivity Within and Between Multiple Spatial Scales. Brain Connect. 12(7): 617-628 (2022) - [j17]Min Zhao, Weizheng Yan
An attention-based hybrid deep learning framework integrating brain connectivity and activity of resting-state functional MRI data. Medical Image Anal. 78: 102413 (2022) - [j16]Armin Iraji
Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping. NeuroImage 251: 119013 (2022) - [j15]Usman Mahmood
Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI. NeuroImage 264: 119737 (2022) - [j14]Ishaan Batta
Building Models of Functional Interactions Among Brain Domains that Encode Varying Information Complexity: A Schizophrenia Case Study. Neuroinformatics 20(3): 777-791 (2022) - [c31]Giorgio Dolci
A deep generative multimodal imaging genomics framework for Alzheimer's disease prediction. BIBE 2022: 41-44 - [c30]Zening Fu, Mustafa S. Salman, Jingyu Liu, Vince D. Calhoun:
Functional Connectivity Stability: A Signature of Neurocognitive Development and Psychiatric Problems in Children. EMBC 2022: 251-254 - [c29]Xinhui Li, Eloy Geenjaar, Zening Fu, Sergey M. Plis, Vince D. Calhoun:
Mind the gap: functional network connectivity interpolation between schizophrenia patients and controls using a variational autoencoder. EMBC 2022: 1477-1480 - [c28]Weizheng Yan, Zening Fu, Jing Sui, Vince D. Calhoun:
'Harmless' adversarial network harmonization approach for removing site effects and improving reproducibility in neuroimaging studies. EMBC 2022: 1859-1862 - [c27]Yuda Bi, Anees Abrol, Zening Fu, Vince D. Calhoun:
Deep Learning Prediction and Visualization of Gender Related Brain Changes from Longitudinal Structural MRI Data in the ABCD Study. EMBC 2022: 3814-3817 - [c26]Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun:
Learning Active Multimodal Subspaces in the Brain. EMBC 2022: 3822-3825 - [c25]Usman Mahmood, Zening Fu, Vince D. Calhoun
Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. IJCNN 2022: 1-10 - [c24]Rekha Saha, Debbrata K. Saha, Md Abdur Rahaman, Zening Fu, Vince D. Calhoun
Longitudinal Whole-Brain Functional Network Change Patterns Over A Two-Year Period In The ABCD Data. ISBI 2022: 1-4 - [c23]Md Abdur Rahaman
Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics Data. MLSP 2022: 1-6 - [i10]Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. CoRR abs/2202.02393 (2022) - [i9]Zafar Iqbal, Usman Mahmood, Zening Fu, Sergey M. Plis:
Self-Supervised Mental Disorder Classifiers via Time Reversal. CoRR abs/2211.16398 (2022) - 2021
- [j13]Usman Mahmood
A Deep Learning Model for Data-Driven Discovery of Functional Connectivity. Algorithms 14(3): 75 (2021) - [j12]Kaicheng Li, Zening Fu, Xiao Luo, Qingze Zeng, Peiyu Huang, Minming Zhang, Vince D. Calhoun
The Influence of Cerebral Small Vessel Disease on Static and Dynamic Functional Network Connectivity in Subjects Along Alzheimer's Disease Continuum. Brain Connect. 11(3): 189-200 (2021) - [j11]Mohammad S. Eslampanah Sendi
Abnormal Dynamic Functional Network Connectivity Estimated from Default Mode Network Predicts Symptom Severity in Major Depressive Disorder. Brain Connect. 11(10): 838-849 (2021) - [j10]Li Zhang, Zening Fu, Wenwen Zhang, Gan Huang, Zhen Liang, Linling Li, Bharat B. Biswal
Accessing dynamic functional connectivity using l0-regularized sparse-smooth inverse covariance estimation from fMRI. Neurocomputing 443: 147-161 (2021) - [j9]Zening Fu
Dynamic state with covarying brain activity-connectivity: On the pathophysiology of schizophrenia. NeuroImage 224: 117385 (2021) - [c22]Thomas DeRamus
Stability of functional network connectivity (FNC) values across multiple spatial normalization pipelines in spatially constrained independent component analysis. BIBE 2021: 1-6 - [c21]Mustafa S. Salman, Eric Verner, Henry Jeremy Bockholt, Zening Fu, Vince D. Calhoun
Machine Learning Predicts Treatment Response in Bipolar & Major Depression Disorders. BIBE 2021: 1-6 - [c20]Md Abdur Rahaman
Multi-modal deep learning of functional and structural neuroimaging and genomic data to predict mental illness. EMBC 2021: 3267-3272 - [c19]Eloy Geenjaar, Noah Lewis, Zening Fu, Rohan Venkatdas, Sergey M. Plis, Vince D. Calhoun
Fusing multimodal neuroimaging data with a variational autoencoder. EMBC 2021: 3630-3633 - [c18]Bhaskar Ray, Kuaikuai Duan, Jiayu Chen, Zening Fu, Pranav Suresh, Sarah Johnson, Vince D. Calhoun
Multimodal Brain Age Prediction with Feature Selection and Comparison. EMBC 2021: 3858-3864 - [c17]Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun
A Multimodal Learning Framework to Study Varying Information Complexity in Structural and Functional Sub-Domains in Schizophrenia. ISBI 2021: 994-998 - [i8]Eloy Geenjaar, Noah Lewis, Zening Fu, Rohan Venkatdas, Sergey M. Plis, Vince D. Calhoun
Fusing multimodal neuroimaging data with a variational autoencoder. CoRR abs/2105.01128 (2021) - [i7]Usman Mahmood
Brain dynamics via Cumulative Auto-Regressive Self-Attention. CoRR abs/2111.01271 (2021) - [i6]Usman Mahmood
Multi network InfoMax: A pre-training method involving graph convolutional networks. CoRR abs/2111.01276 (2021) - [i5]Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
A deep learning model for data-driven discovery of functional connectivity. CoRR abs/2112.04013 (2021) - 2020
- [j8]Rongtao Jiang
Task-induced brain connectivity promotes the detection of individual differences in brain-behavior relationships. NeuroImage 207 (2020) - [c16]Haleh Falakshahi, Hooman Rokham, Zening Fu, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah C. McEwen, Steven G. Potkin, Adrian Preda
Time-varying Graphs: A Method to Identify Abnormal Integration and Disconnection in Functional Brain Connectivity with Application to Schizophrenia. BIBE 2020: 417-424 - [c15]Ishaan Batta, Anees Abrol, Zening Fu, Vince D. Calhoun
Varying Information Complexity in Functional Domain Interactions in Schizophrenia. BIBE 2020: 1042-1047 - [c14]Elaheh Zendehrouh, Mohammad S. Eslampanah Sendi, Jing Sui
Aberrant Functional Network Connectivity Transition Probability in Major Depressive Disorder. EMBC 2020: 1493-1496 - [c13]Armin Iraji
Functional Multi-Connectivity: A Novel Approach To Assess Multi-Way Entanglement Between Networks and Voxels. ISBI 2020: 1698-1701 - [c12]Usman Mahmood
Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations. MICCAI (7) 2020: 407-417 - [c11]Mohammad S. Eslampanah Sendi, Elaheh Zendehrouh, Zening Fu, Babak Mahmoudi, Robyn L. Miller, Vince D. Calhoun
A Machine Learning Model for Exploring Aberrant Functional Network Connectivity Transition in Schizophrenia. SSIAI 2020: 112-115 - [i4]Usman Mahmood
Whole MILC: generalizing learned dynamics across tasks, datasets, and populations. CoRR abs/2007.16041 (2020)
2010 – 2019
- 2019
- [j7]Ahmed M. Anter
A robust swarm intelligence-based feature selection model for neuro-fuzzy recognition of mild cognitive impairment from resting-state fMRI. Inf. Sci. 503: 670-687 (2019) - [j6]Zening Fu, Yiheng Tu, Xin Di
Transient increased thalamic-sensory connectivity and decreased whole-brain dynamism in autism. NeuroImage 190: 191-204 (2019) - [c10]Alex Fedorov
Prediction of Progression to Alzheimer's disease with Deep InfoMax. BHI 2019: 1-5 - [c9]Anees Abrol, Zening Fu, Yuhui Du, Vince D. Calhoun
Multimodal Data Fusion of Deep Learning and Dynamic Functional Connectivity Features to Predict Alzheimer's Disease Progression. EMBC 2019: 4409-4413 - [c8]Tiantian Li, Zening Fu, Xia Liu, Shile Qi, Vince D. Calhoun
Multimodal Neuroimaging Patterns Associated with Social Responsiveness Impairment in Autism: A Replication Study. ISBI 2019: 409-413 - [i3]Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun:
Prediction of Progression to Alzheimer's disease with Deep InfoMax. CoRR abs/1904.10931 (2019) - [i2]Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Sergey M. Plis:
Transfer Learning of fMRI Dynamics. CoRR abs/1911.06813 (2019) - [i1]Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Vince D. Calhoun, Sergey M. Plis:
Learnt dynamics generalizes across tasks, datasets, and populations. CoRR abs/1912.03130 (2019) - 2018
- [j5]Yiheng Tu, Zening Fu, Ao Tan, Gan Huang, Li Hu, Yeung Sam Hung, Zhiguo Zhang:
A novel and effective fMRI decoding approach based on sliced inverse regression and its application to pain prediction. Neurocomputing 273: 373-384 (2018) - [j4]Zening Fu, Yiheng Tu, Xin Di
Characterizing dynamic amplitude of low-frequency fluctuation and its relationship with dynamic functional connectivity: An application to schizophrenia. NeuroImage 180(Part): 619-631 (2018) - [j3]Yuhui Du, Susanna Fryer, Zening Fu, Dongdong Lin, Jing Sui
Dynamic functional connectivity impairments in early schizophrenia and clinical high-risk for psychosis. NeuroImage 180(Part): 632-645 (2018) - [j2]Rongtao Jiang
Connectome-based individualized prediction of temperament trait scores. NeuroImage 183: 366-374 (2018) - 2017
- [c7]Ao Tan, Yiheng Tu, Zening Fu, Gan Huang, Yeung Sam Hung, Zhiguo Zhang:
A least across-segment variance (LASV) method for the correction of EEG-fMRI desynchronization. NER 2017: 5-8 - 2015
- [c6]Zening Fu, Sheng Han, Ao Tan, Yiheng Tu, Zhiguo Zhang:
L0-regularized time-varying sparse inverse covariance estimation for tracking dynamic fMRI brain networks. EMBC 2015: 1496-1499 - [c5]Ao Tan, Zening Fu, Yiheng Tu, Yeung Sam Hung, Zhiguo Zhang:
Joint source separation of simultaneous EEG-fMRI recording in two experimental conditions using common spatial patterns. EMBC 2015: 2633-2636 - [c4]Yiheng Tu, Ao Tan, Zening Fu, Yeung Sam Hung, Li Hu, Zhiguo Zhang:
Supervised nonlinear dimension reduction of functional magnetic resonance imaging data using Sliced Inverse Regression. EMBC 2015: 2641-2644 - 2014
- [j1]Zening Fu, Shing-Chow Chan, Xin Di
Adaptive Covariance Estimation of Non-Stationary Processes and its Application to Infer Dynamic Connectivity From fMRI. IEEE Trans. Biomed. Circuits Syst. 8(2): 228-239 (2014) - 2013
- [c3]Zhiguo Zhang, Zening Fu, Shing-Chow Chan, Y. S. Hung, G. Motta, Xin Di
Adaptive window selection in estimating dynamic functional connectivity of resting-state fMRI. ICICS 2013: 1-4 - [c2]Zening Fu, Xin Di
Time-varying correlation coefficients estimation and its application to dynamic connectivity analysis of fMRI. EMBC 2013: 2944-2947 - [c1]Zening Fu, Zhiguo Zhang, Shing-Chow Chan:
Estimation of time-varying autocorrelation and its application to time-frequency analysis of nonstationary signals. ISCAS 2013: 1524-1527
Coauthor Index
Vince D. Calhoun
aka: Vincent D. Calhoun
aka: Vincent D. Calhoun
[j25] [j24] [j23] [j22] [j21] [c47] [c46] [c45] [c44] [c43] [c42] [c41] [i13] [i12] [i11] [j20] [c39] [c38] [c37] [c36] [c35] [c33] [c32] [j19] [j18] [j17] [j16] [j15] [j14] [c31] [c30] [c29] [c28] [c27] [c26] [c25] [c24] [c23] [i10] [j13] [j12] [j11] [j10] [j9] [c22] [c21] [c20] [c19] [c18] [c17] [i8] [i7] [i6] [i5] [j8] [c16] [c15] [c14] [c13] [c12] [c11] [i4] [j6] [c10] [c9] [c8] [i3] [i1] [j4] [j3] [j2]
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last updated on 2025-01-20 22:58 CET by the dblp team
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