Vince D. Calhoun

ORCID

Publication Activity (10 Years)

Years Active: 1999-2024
Publications (10 Years): 520

Top Venues

Publications

Longyun Chen, Chen Qiao, Kai Ren, Gang Qu, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang
Explainable spatio-temporal graph evolution learning with applications to dynamic brain network analysis during development. NeuroImage 298 (2024)
Kelly Rootes-Murdy, Sandeep R. Panta, Ross Kelly, Javier Tomas Romero, Yann Quidé, Murray J. Cairns, C. M. Loughland, Vaughan J. Carr, Stanley V. Catts, Assen Jablensky, Melissa J. Green, Frans Henskens, Dylan Kiltschewskij, Patricia T. Michie, Bryan J. Mowry, Christos Pantelis, Paul E. Rasser, William R. Reay, Ulrich Schall, Rodney J. Scott, Oliver J. Watkeys, Gloria M. P. Roberts, Philip B. Mitchell, Janice M. Fullerton, Bronwyn J. Overs, Masataka Kikuchi, Ryota Hashimoto, Junya Matsumoto, Masaki Fukunaga, Perminder S. Sachdev, Henry Brodaty, Wei Wen, Jiyang Jiang, Negar Fani, Timothy D. Ely, Adriana Lorio, Jennifer S. Stevens, Kerry J. Ressler, Tanja Jovanovic, Sanne J. H. van Rooij, Lydia M. Federmann, Christiane Jockwitz, Alexander Teumer, Andreas J. Forstner, Svenja Caspers, Sven Cichon, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun
Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC. Patterns 5 (7) (2024)
Giorgio Dolci, Charles A. Ellis, Federica Cruciani, Lorenza Brusini, Anees Abrol, Ilaria Boscolo Galazzo, Gloria Menegaz, Vince D. Calhoun
Multimodal MRI-based Detection of Amyloid Status in Alzheimer's Disease Continuum. CoRR (2024)
Riyasat Ohib, Bishal Thapaliya, Gintare Karolina Dziugaite, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis
Unmasking Efficiency: Learning Salient Sparse Models in Non-IID Federated Learning. CoRR (2024)
Ishaan Batta, Anees Abrol, Vince D. Calhoun
A Novel Deep Subspace Learning Framework to Automatically Uncover Assessment-Specific Independent Brain Networks. CISS (2024)
Nagur Shareef Shaik, Teja Krishna Cherukuri, Vince D. Calhoun, Dong Hye Ye
Multi-modal Imaging Genomics Transformer: Attentive Integration of Imaging with Genomic Biomarkers for Schizophrenia Classification. CoRR (2024)
Sisi Jiang, Haonan Pei, Junxia Chen, Hechun Li, Zetao Liu, Yuehan Wang, Jinnan Gong, Sheng Wang, Qifu Li, Mingjun Duan, Vince D. Calhoun, Dezhong Yao, Cheng Luo
Striatum- and Cerebellum-Modulated Epileptic Networks Varying Across States with and without Interictal Epileptic Discharges. Int. J. Neural Syst. 34 (4) (2024)
Zening Fu, Ishaan Batta, Lei Wu, Anees Abrol, Oktay Agcaoglu, Mustafa S. Salman, Yuhui Du, Armin Iraji, Sarah Shultz, Jing Sui, Vince D. Calhoun
Searching Reproducible Brain Features using NeuroMark: Templates for Different Age Populations and Imaging Modalities. NeuroImage 292 (2024)
Qiang Li, Masoud Seraji, Vince D. Calhoun, Armin Iraji
Complexity Measures of Psychotic Brain Activity In The FMRI Signal. SSIAI (2024)
Ashkan Faghiri, Armin Iraji, Tülay Adali, Vince D. Calhoun
Analysis of High-Order Brain Networks Resolved in Time and Frequency Using CP Decomposition. ICASSP (2024)
Rekha Saha, Debbrata K. Saha, Md Abdur Rahaman, Zening Fu, Jingyu Liu, Vince D. Calhoun
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) (2024)
M. Moein Esfahani, Hossein Sadati, Vince D. Calhoun
Optimizing Brain-Computer Interface Performance: Advancing EEG Signals Channel Selection through Regularized CSP and SPEA II Multi-Objective Optimization. CoRR (2024)
Bishal Thapaliya, Robyn L. Miller, Jiayu Chen, Yu-Ping Wang, Esra Akbas, Ram Sapkota, Bhaskar Ray, Pranav Suresh, Santosh Ghimire, Vince D. Calhoun, Jingyu Liu
DSAM: A Deep Learning Framework for Analyzing Temporal and Spatial Dynamics in Brain Networks. CoRR (2024)
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 (2024)
Bradley T. Baker, Barak A. Pearlmutter, Robyn L. Miller, Vince D. Calhoun, Sergey M. Plis
Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse. CoRR (2024)
Trung Vu, Hanlu Yang, Francisco Laport, Ben Gabrielson, Vince D. Calhoun, Tülay Adali
A Robust and Scalable Method with an Analytic Solution for Multi-Subject FMRI Data Analysis. ICASSP (2024)
Isabell Lehmann, Tanuj Hasija, Ben Gabrielson, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Tülay Adali
Identifying the Relationship Structure Among Multiple Datasets Using Independent Vector Analysis: Application to Multi-Task fMRI Data. IEEE Access 12 (2024)
Yutong Gao, Charles A. Ellis, Vince D. Calhoun, Robyn L. Miller
Improving Age Prediction: Utilizing LSTM-Based Dynamic Forecasting For Data Augmentation in Multivariate Time Series Analysis. SSIAI (2024)
Reihaneh Hassanzadeh, Anees Abrol, Hamid Reza Hassanzadeh, Vince D. Calhoun
Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers. CoRR (2024)
H. Yang, Meiby Ortiz-Bouza, T. Vu, Francisco Laport, Vince D. Calhoun, Selin Aviyente, Tülay Adali
Subgroup Identification Through Multiplex Community Structure Within Functional Connectivity Networks. ICASSP (2024)
Yuda Bi, Anees Abrol, Sihan Jia, Jing Sui, Vince D. Calhoun
Gray matters: ViT-GAN framework for identifying schizophrenia biomarkers linking structural MRI and functional network connectivity. NeuroImage 297 (2024)
Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, Girish Mittapalle, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun
Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. NeuroImage 285 (2024)
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 (2024)
Nagur Shareef Shaik, Teja Krishna Cherukuri, Vince D. Calhoun, Dong Hye Ye
Spatial Sequence Attention Network for Schizophrenia Classification from Structural Brain MR Images. CoRR (2024)
Gang Qu, Anton Orlichenko, Junqi Wang, Gemeng Zhang, Li Xiao, Kun Zhang, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang
Interpretable Cognitive Ability Prediction: A Comprehensive Gated Graph Transformer Framework for Analyzing Functional Brain Networks. IEEE Trans. Medical Imaging 43 (4) (2024)
Yue Han, Qiu-Hua Lin, Li-Dan Kuang, Bin-Hua Zhao, Xiao-Feng Gong, Fengyu Cong, Yu-Ping Wang, Vince D. Calhoun
A core tensor sparsity enhancement method for solving Tucker-2 model of multi-subject fMRI data. Biomed. Signal Process. Control. 95 (2024)
Weizheng Yan, Zening Fu, Rongtao Jiang, Jing Sui, Vince D. Calhoun
Maximum Classifier Discrepancy Generative Adversarial Network for Jointly Harmonizing Scanner Effects and Improving Reproducibility of Downstream Tasks. IEEE Trans. Biomed. Eng. 71 (4) (2024)
David Sutherland Blair, Robyn L. Miller, Vince D. Calhoun
A Dynamic Entropy Approach Reveals Reduced Functional Network Connectivity Trajectory Complexity in Schizophrenia. Entropy 26 (7) (2024)
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) (2024)
Bradley T. Baker, Vince D. Calhoun, Sergey M. Plis
Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging. CoRR (2024)
Robyn L. Miller, Victor M. Vergara, Vince D. Calhoun
Markov Spatial Flows in Bold FMRI: A Novel Lens on the Bold Signal Applied To an Imaging Study of Schizophrenia. SSIAI (2024)
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 (2024)
Steven Laureys, Marc Raichle, Karl J. Friston, Susan L. Whitfield-Gabrieli, Jennifer L. Whitwell, Vince D. Calhoun, Linda Douw, Mélanie Boly
A Roundtable Discussion on Brain Connectivity. Brain Connect. 14 (5) (2024)
Natalia Maksymchuk, Robyn L. Miller, Vince D. Calhoun
Distribution of Connectivity Strengths Across Functional Regions has Higher Entropy in Schizophrenia Patients than in Controls. SSIAI (2024)
Ram Sapkota, Bishal Thapaliya, Pranav Suresh, Bhaskar Ray, Vince D. Calhoun, Jingyu Liu
Multimodal Imaging Feature Extraction with Reference Canonical Correlation Analysis Underlying Intelligence. ICASSP (2024)
Irina Belyaeva, Ben Gabrielson, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali
Learning Spatiotemporal Brain Dynamics in Adolescents via Multimodal MEG and fMRI Data Fusion Using Joint Tensor/Matrix Decomposition. IEEE Trans. Biomed. Eng. 71 (7) (2024)
Yuda Bi, Anees Abrol, Jing Sui, Vince D. Calhoun
Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs. ICASSP (2024)
Anton Orlichenko, Gang Qu, Ziyu Zhou, Anqi Liu, Hong-Wen Deng, Zhengming Ding, Julia M. Stephen, Tony W. Wilson, Vince D. Calhoun, Yu-Ping Wang
A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds. CoRR (2024)
Sunitha Basodi, Rajikha Raja, Harshvardhan Gazula, Javier Tomas Romero, Sandeep R. Panta, Thomas Maullin-Sapey, Thomas E. Nichols, Vince D. Calhoun
Decentralized Mixed Effects Modeling in COINSTAC. Neuroinformatics 22 (2) (2024)
Wei Wang, Li Xiao, Gang Qu, Vince D. Calhoun, Yu-Ping Wang, Xiaoyan Sun
Multiview hyperedge-aware hypergraph embedding learning for multisite, multiatlas fMRI based functional connectivity network analysis. Medical Image Anal. 94 (2024)
Yutong Gao, Noah Lewis, Vince D. Calhoun, Robyn L. Miller
Interpretable LSTM model reveals transiently-realized patterns of dynamic brain connectivity that predict patient deterioration or recovery from very mild cognitive impairment. Comput. Biol. Medicine 161 (2023)
Meenu Ajith, Vince D. Calhoun
Functional Network Connectivity Based Mental Health Category Prediction from Rest-fMRI Data. ISBI (2023)
Yujia Xie, Xinhui Li, Vince D. Calhoun
Predictive Sparse Manifold Transform. CoRR (2023)
Elaheh Zendehrouh, Mohammad S. Eslampanah Sendi, Vince D. Calhoun
Towards a multimodal neuroimaging-based risk score for Alzheimer's disease by combining clinical and large N>37000 population data. EMBC (2023)
Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
Glacier: Glass-Box Transformer for Interpretable Dynamic Neuroimaging. ICASSP (2023)
Robyn L. Miller, Victor M. Vergara, Vince D. Calhoun
Hyperlocal Spatial Flows in BOLD fMRI Expose Novel Brain-Based Correlates of Schizophrenia. EMBC (2023)
Yuhui Du, Yating Guo, Vince D. Calhoun
How Does Aging Affect Whole-brain Functional Network Connectivity? Evidence from An ICA Method. EMBC (2023)
Mark D. LoPresto, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Tülay Adali
Fusion of Multi-Modal Neuroimaging Data and Association With Cognitive Data. ICASSP Workshops (2023)
Ben Gabrielson, Mingyu Sun, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Tülay Adali
Independent Vector Analysis with Multivariate Gaussian Model: a Scalable Method by Multilinear Regression. ICASSP (2023)
Debbrata Kumar Saha, Anastasia Bohsali, Rekha Saha, Ihab Hajjar, Vince D. Calhoun
A Multivariate Method for Estimating and comparing whole brain functional connectomes from fMRI and PET data. EMBC (2023)
Francisco Laport, Trung Vu, Hanlu Yang, Vince D. Calhoun, Tülay Adali
Reproducibility in Joint Blind Source Separation: Application to fMRI Analysis. ACSSC (2023)
Qiang Li, Shujian Yu, Kristoffer H. Madsen, Vince D. Calhoun, Armin Iraji
Higher-Order Organization in the Human Brain From Matrix-Based Rényi's Entropy. ICASSP Workshops (2023)
Dylan Martin, Sunitha Basodi, Sandeep R. Panta, Kelly Rootes-Murdy, Paul Prae, Anand D. Sarwate, Ross Kelly, Javier Romero, Bradley T. Baker, Harshvardhan Gazula, Henry Jeremy Bockholt, Jessica A. Turner, Nathalia Bianchini Esper, Alexandre R. Franco, Sergey M. Plis, Vince D. Calhoun
Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility. Frontiers Neuroinformatics 17 (2023)
Noah Lewis, Armin Iraji, Robyn L. Miller, Vince D. Calhoun
Topological Correction of Subject-Level Intrinsic Connectivity Networks. ISBI (2023)
Giorgio Dolci, Md Abdur Rahaman, Ilaria Boscolo Galazzo, Federica Cruciani, Anees Abrol, Jiayu Chen, Zening Fu, Kuaikuai Duan, Gloria Menegaz, Vince D. Calhoun
Deep Generative Transfer Learning Predicts Conversion To Alzheimer'S Disease From Neuroimaging Genomics Data. ICASSP Workshops (2023)
Lan Yang, Chen Qiao, Huiyu Zhou, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang
Explainable Multimodal Deep Dictionary Learning to Capture Developmental Differences From Three fMRI Paradigms. IEEE Trans. Biomed. Eng. 70 (8) (2023)
Robyn L. Miller, Victor M. Vergara, Helen Petropoulos, Vince D. Calhoun
Local Spatial Flow Strengths in Bold FMRI are Strongly Impacted by Schizophrenia. ICASSP Workshops (2023)
Giorgio Dolci, Federica Cruciani, Ilaria Boscolo Galazzo, Vince D. Calhoun, Gloria Menegaz
Objective Assessment of the Bias Introduced by Baseline Signals in XAI Attribution Methods. MetroXRAINE (2023)
Chen Qiao, Bin Gao, Yuechen Liu, Xin-Yu Hu, Wenxing Hu, Vince D. Calhoun, Yu-Ping Wang
Deep learning with explainability for characterizing age-related intrinsic differences in dynamic brain functional connectivity. Medical Image Anal. 90 (2023)
Xinhui Li, Daniel Khosravinezhad, Vince D. Calhoun, Rogers F. Silva
Evaluating Trade-Offs in IVA of Multimodal Neuroimaging using Cross-Platform Multidataset Independent Subspace Analysis. ISBI (2023)
Ayush Kanyal, Srinivas Kandula, Vince D. Calhoun, Dong Hye Ye
Multi-Modal Deep Learning on Imaging Genetics for Schizophrenia Classification. ICASSP Workshops (2023)
Anton Orlichenko, Gang Qu, Gemeng Zhang, Binish Patel, Tony W. Wilson, Julia M. Stephen, Vince D. Calhoun, Yu-Ping Wang
Latent Similarity Identifies Important Functional Connections for Phenotype Prediction. IEEE Trans. Biomed. Eng. 70 (6) (2023)
Oktay Agcaoglu, Rogers F. Silva, Deniz Alaçam, Vince D. Calhoun
A Multi-dimensional Joint ICA Model with Gaussian Copula. ICIAP Workshops (2) (2023)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
A Novel Explainable Fuzzy Clustering Approach for fMRI Dynamic Functional Network Connectivity Analysis. EMBC (2023)
Haleh Falakshahi, Hooman Rokham, Robyn L. Miller, Jean Liu, Vince D. Calhoun
Network Differential in Gaussian Graphical Models from Multimodal Neuroimaging Data. EMBC (2023)
Sunitha Basodi, Rajikha Raja, Harshvardhan Gazula, Javier Romero, Sandeep R. Panta, Vince D. Calhoun
Federated Linear Mixed Effects Modeling for Voxel-Based Morphometry. ISBI (2023)
Chan Aek Panichvatana, Jiayu Chen, Bradley T. Baker, Bishal Thapaliya, Vince D. Calhoun, Jingyu Liu
Decentralized Parallel Independent Component Analysis for Multimodal, Multisite Data. EMBC (2023)
Sir-Lord Wiafe, Zening Fu, Vince D. Calhoun, Ashkan Faghiri
Phase and amplitude, two sides of functional connectivity. EMBC (2023)
Hanlu Yang, Fateme Ghayem, Ben Gabrielson, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Tülay Adali
Constrained Independent Component Analysis Based on Entropy Bound Minimization for Subgroup Identification from Multi-subject fMRI Data. ICASSP (2023)
Fateme Ghayem, H. Yang, Furkan Kantar, S.-J. Kim, Vince D. Calhoun, Tülay Adali
New Interpretable Patterns and Discriminative Features from Brain Functional Network Connectivity using Dictionary Learning. ICASSP (2023)
Hanlu Yang, Ben Gabrielson, Vince D. Calhoun, Tülay Adali
REGRESSION-ASSISTED INDEPENDENT VECTOR ANALYSIS: A SOLUTION TO LARGE-SCALE FMRI DATA ANALYSIS. ACSSC (2023)
Yuhui Du, Fulin Wu, Ju Niu, Vince D. Calhoun
An Adaptive Semi-Supervised Deep Clustering and Its Application to Identifying Biotypes of Psychiatric Disorders. ISBI (2023)
Xiang Li, Ming Xu, Rongtao Jiang, Xuemei Li, Vince D. Calhoun, Xinyu Zhou, Jing Sui
ICA-based Individualized Differential Structure Similarity Networks for Predicting Symptom Scores in Adolescents with Major Depressive Disorder. EMBC (2023)
Rekha Saha, Debbrata K. Saha, Zening Fu, Rogers F. Silva, Vince D. Calhoun
Functional and Structural Longitudinal Change Patterns in Adolescent Brain. EMBC (2023)
Xiang Li, Sheri L. Towe, Ryan P. Bell, Rongtao Jiang, Shana A. Hall, Vince D. Calhoun, Christina S. Meade, Jing Sui
The Individualized Prediction of Neurocognitive Function in People Living With HIV Based on Clinical and Multimodal Connectome Data. IEEE J. Biomed. Health Informatics 27 (4) (2023)
Yue Han, Qiu-Hua Lin, Li-Dan Kuang, Ying-Guang Hao, Wei-Xing Li, Xiao-Feng Gong, Vince D. Calhoun
Extraction of One Time Point Dynamic Group Features via Tucker Decomposition of Multi-subject FMRI Data: Application to Schizophrenia. ICONIP (9) (2023)
Irina Belyaeva, Ben Gabrielson, Yu-Ping Wang, Tony W. Wilson, Vince D. Calhoun, Julia M. Stephen, Tülay Adali
Multi-Subject Analysis for Brain Developmental Patterns Discovery via Tensor Decomposition of MEG Data. Neuroinformatics 21 (1) (2023)
Yutong Gao, Charles A. Ellis, Vince D. Calhoun, Robyn L. Miller
Improving age prediction: Utilizing LSTM-based dynamic forecasting for data augmentation in multivariate time series analysis. CoRR (2023)
Riyasat Ohib, Bishal Thapaliya, Pratyush Gaggenapalli, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis
SalientGrads: Sparse Models for Communication Efficient and Data Aware Distributed Federated Training. CoRR (2023)
Mohammad S. Eslampanah Sendi, Elaheh Zendehrouh, Zening Fu, Jingyu Liu, Yuhui Du, Elizabeth Mormino, David H. Salat, Vince D. Calhoun, Robyn L. Miller
Disrupted Dynamic Functional Network Connectivity Among Cognitive Control Networks in the Progression of Alzheimer's Disease. Brain Connect. 13 (6) (2023)
Charles A. Ellis, Mohammad S. Eslampanah Sendi, Rongen Zhang, Darwin A. Carbajal, May D. Wang, Robyn L. Miller, Vince D. Calhoun
Novel methods for elucidating modality importance in multimodal electrophysiology classifiers. Frontiers Neuroinformatics 17 (2023)
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)
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)
Faming Xu, Chen Qiao, Huiyu Zhou, Vince D. Calhoun, Julia M. Stephen, Tony W. Wilson, Yu-Ping Wang
An explainable autoencoder with multi-paradigm fMRI fusion for identifying differences in dynamic functional connectivity during brain development. Neural Networks 159 (2023)
Eloy Geenjaar, Donghyun Kim, Riyasat Ohib, Marlena Duda, Amrit Kashyap, Sergey M. Plis, Vince D. Calhoun
Learning low-dimensional dynamics from whole-brain data improves task capture. CoRR (2023)
Md. Mahfuzur Rahman, Vince D. Calhoun, Sergey M. Plis
Looking deeper into interpretable deep learning in neuroimaging: a comprehensive survey. CoRR (2023)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
Neuropsychiatric Disorder Subtyping Via Clustered Deep Learning Classifier Explanations. EMBC (2023)
Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
A Convolutional Autoencoder-based Explainable Clustering Approach for Resting-State EEG Analysis. EMBC (2023)
Mahshid Fouladivanda, Armin Iraji, Lei Wu, Vince D. Calhoun
Joint Structural and Functional Connectivity Learning Based Independent Component Analysis. MLSP (2023)
Mustafa S. Salman, Armin Iraji, Noah Lewis, Vince D. Calhoun
Topological Characteristics of 5d Spatially Dynamic Brain Networks in Schizophrenia. ISBI (2023)
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)
Abhinav Sattiraju, Charles A. Ellis, Robyn L. Miller, Vince D. Calhoun
An Explainable and Robust Deep Learning Approach for Automated Electroencephalography-Based Schizophrenia Diagnosis. BIBE (2023)
Ishaan Batta, Anees Abrol, Vince D. Calhoun
A Multimodal Deep Learning Approach for Automated Detection and Characterization of Distinctly Salient Features of Alzheimers Disease. ISBI (2023)
Kuaikuai Duan, Rogers F. Silva, Jingyu Liu, Oktay Agcaoglu, Vince D. Calhoun
Any-Way Independent Component Analysis with Reference. ISBI (2023)
Bishal Thapaliya, Esra Akbas, Jiayu Chen, Raam Sapkota, Bhaskar Ray, Pranav Suresh, Vince D. Calhoun, Jingyu Liu
Brain Networks and Intelligence: A Graph Neural Network Based Approach to Resting State fMRI Data. CoRR (2023)
Mingyu Sun, Ben Gabrielson, Mohammad Abu Baker Siddique Akhonda, Hanlu Yang, Francisco Laport, Vince D. Calhoun, Tülay Adali
A Scalable Approach to Independent Vector Analysis by Shared Subspace Separation for Multi-Subject fMRI Analysis. Sensors 23 (11) (2023)
Ying Xing, Peter V. Kochunov, Theo G. M. van Erp, Tianzhou Ma, Vince D. Calhoun, Yuhui Du
A Novel Neighborhood Rough Set-Based Feature Selection Method and Its Application to Biomarker Identification of Schizophrenia. IEEE J. Biomed. Health Informatics 27 (1) (2023)
Yuda Bi, Anees Abrol, Jing Sui, Vince D. Calhoun
Cross-Modal Synthesis of Structural MRI and Functional Connectivity Networks via Conditional ViT-GANs. CoRR (2023)
Biozid Bostami, Mukesh Dhamala, Tülay Adali, Vince D. Calhoun, Armin Iraji
Spatial Dynamic Propagation of Network Activity in Resting fMRI Data. ISBI (2023)
R. A. Borsoi, Isabell Lehmann, Mohammad A. B. S. Akhonda, Vince D. Calhoun, Konstantin Usevich, David Brie, Tülay Adali
Coupled CP Tensor Decomposition with Shared and Distinct Components for Multi-Task Fmri Data Fusion. ICASSP (2023)

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Publication Activity (10 Years)

Top Topics

Top Venues

Vince D. Calhoun