Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging data. - Sung C. Jun; John S. George; E. Juliana Paré-Blagoev; Sergey M. Plis; Douglas M. Ranken; David M. Schmidt 004; C. C. Wood (NeuroImage, 2005)

A generalized spatiotemporal covariance model for stationary background in analysis of MEG data. - Sergey M. Plis; David M. Schmidt 004; Sung C. Jun; Douglas M. Ranken (EMBC, 2006)

Bayesian brain source imaging based on combined MEG/EEG and fMRI using MCMC. - Sung C. Jun; John S. George; Woohan Kim; E. Juliana Paré-Blagoev; Sergey M. Plis; Douglas M. Ranken; David M. Schmidt 004 (NeuroImage, 2008)

Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks. - Eva Besada-Portas; Sergey M. Plis; Jesús Manuel de la Cruz; Terran Lane (ECML/PKDD (1), 2009)

Efficient Multiplicative Updates for Support Vector Machines. - Vamsi K. Potluru; Sergey M. Plis; Morten Mørup; Vincent D. Calhoun; Terran Lane (SDM, 2009)

Multiplicative updates For Non-Negative Kernel SVM - Vamsi K. Potluru; Sergey M. Plis; Morten Mørup; Vince D. Calhoun; Terran Lane (CoRR, 2009)

Permutations as Angular Data: Efficient Inference in Factorial Spaces. - Sergey M. Plis; Terran Lane; Vince D. Calhoun (ICDM, 2010)

Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks. - Eva Besada-Portas; Sergey M. Plis; Jesús Manuel de la Cruz; Terran Lane (ECML/PKDD (1), 2010)

MEG and fMRI fusion for nonlinear estimation of neural and BOLD signal changes. - Sergey M. Plis; Vince D. Calhoun; Tom Eichele; Michael P. Weisend; Terran Lane (Frontiers Neuroinformatics, 2010)

Sparseness and a reduction from Totally Nonnegative Least Squares to SVM. - Vamsi K. Potluru; Sergey M. Plis; Shuang Luan; Vince D. Calhoun; Thomas P. Hayes (IJCNN, 2011)

Effective connectivity analysis of fMRI and MEG data collected under identical paradigms. - Sergey M. Plis; Michael P. Weisend; Eswar Damaraju; Tom Eichele; Andy R. Mayer; Vincent P. Clark; Terran Lane; Vince D. Calhoun (Comput. Biol. Medicine, 2011)

Directional Statistics on Permutations. - Sergey M. Plis; Stephen McCracken; Terran Lane; Vince D. Calhoun (AISTATS, 2011)

Correlated Noise: How it Breaks NMF, and What to Do About it. - Sergey M. Plis; Vamsi K. Potluru; Terran Lane; Vince D. Calhoun (J. Signal Process. Syst., 2011)

Block Coordinate Descent for Sparse NMF - Vamsi K. Potluru; Sergey M. Plis; Jonathan Le Roux; Barak A. Pearlmutter; Vince D. Calhoun; Thomas P. Hayes (ICLR (Poster), 2013)

Multidataset independent subspace analysis extends independent vector analysis. - Rogers F. Silva; Sergey M. Plis; Tülay Adali; Vince D. Calhoun (ICIP, 2014)

The tenth annual MLSP competition: Schizophrenia classification challenge. - Rogers F. Silva; Eduardo Castro; Cota Navin Gupta; Mustafa S. Çetin; Mohammad Arbabshirani; Vamsi K. Potluru; Sergey M. Plis; Vince D. Calhoun (MLSP, 2014)

Deep learning for neuroimaging: a validation study. - Sergey M. Plis; R. Devon Hjelm; Ruslan Salakhutdinov; Vince D. Calhoun (ICLR (Workshop Poster), 2014)

Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation. - Anand D. Sarwate; Sergey M. Plis; Jessica A. Turner; Mohammad Arbabshirani; Vince D. Calhoun (Frontiers Neuroinformatics, 2014)

Impact of autocorrelation on functional connectivity. - Mohammad R. Arbabshirani; Eswar Damaraju; Ronald Phlypo; Sergey M. Plis; Elena A. Allen; Sai Ma; Daniel H. Mathalon; Adrian Preda; Jatin G. Vaidya; Tülay Adali; Vince D. Calhoun (NeuroImage, 2014)

Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks. - R. Devon Hjelm; Vince D. Calhoun; Ruslan Salakhutdinov; Elena A. Allen; Tülay Adali; Sergey M. Plis (NeuroImage, 2014)

Functional and effective connectivity of stopping. - René J. Huster; Sergey M. Plis; Christina F. Lavallee; Vince D. Calhoun; Christoph S. Herrmann (NeuroImage, 2014)

High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia. - Sergey M. Plis; Jing Sui; Terran Lane; Sushmita Roy; Vincent P. Clark; Vamsi K. Potluru; René J. Huster; Andrew Michael; Scott R. Sponheim; Michael P. Weisend; Vince D. Calhoun (NeuroImage, 2014)

A statistically motivated framework for simulation of stochastic data fusion models applied to multimodal neuroimaging. - Rogers F. Silva; Sergey M. Plis; Tülay Adali; Vince D. Calhoun (NeuroImage, 2014)

Generation of synthetic structural magnetic resonance images for deep learning pre-training. - Eduardo Castro; Alvaro Ulloa; Sergey M. Plis; Jessica A. Turner; Vince D. Calhoun (ISBI, 2015)

Large scale collaboration with autonomy: Decentralized data ICA. - Bradley T. Baker; Rogers F. Silva; Vince D. Calhoun; Anand D. Sarwate; Sergey M. Plis (MLSP, 2015)

Deep independence network analysis of structural brain imaging: A simulation study. - Eduardo Castro; R. Devon Hjelm; Sergey M. Plis; Laurent Dinh; Jessica A. Turner; Vince D. Calhoun (MLSP, 2015)

Synthetic structural magnetic resonance image generator improves deep learning prediction of schizophrenia. - Alvaro Ulloa; Sergey M. Plis; Erik B. Erhardt; Vince D. Calhoun (MLSP, 2015)

Rate-Agnostic (Causal) Structure Learning. - Sergey M. Plis; David Danks; Cynthia Freeman; Vince D. Calhoun (NIPS, 2015)

Mesochronal Structure Learning. - Sergey M. Plis; David Danks; Jianyu Yang (UAI, 2015)

Privacy-preserving source separation for distributed data using independent component analysis. - Hafiz Imtiaz; Rogers F. Silva; Bradley T. Baker; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (CISS, 2016)

Data-weighted ensemble learning for privacy-preserving distributed learning. - Liyang Xie; Sergey M. Plis; Anand D. Sarwate (ICASSP, 2016)

Causal Discovery from Subsampled Time Series Data by Constraint Optimization. - Antti Hyttinen; Sergey M. Plis; Matti Järvisalo; Frederick Eberhardt; David Danks (Probabilistic Graphical Models, 2016)

Multimodal fusion of brain structural and functional imaging with a deep neural machine translation approach. - Md Faijul Amin; Sergey M. Plis; Eswar Damaraju; R. Devon Hjelm; Kyunghyun Cho; Vince D. Calhoun (SSIAI, 2016)

Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data. - R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (CoRR, 2016)

Recurrent Neural Networks for Spatiotemporal Dynamics of Intrinsic Networks from fMRI Data. - R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (CoRR, 2016)

A Tool for Interactive Data Visualization: Application to Over 10, 000 Brain Imaging and Phantom MRI Data Sets. - Sandeep R. Panta; Runtang Wang; Jill Fries; Ravi Kalyanam; Nicole K. Speer; Marie T. Banich; Kent A. Kiehl; Margaret D. King; Michael P. Milham; Tor D. Wager; Jessica A. Turner; Sergey M. Plis; et al. (Frontiers Neuroinformatics, 2016)

Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling. - Rogers F. Silva; Sergey M. Plis; Jing Sui; Marios S. Pattichis; Tülay Adali; Vince D. Calhoun (IEEE J. Sel. Top. Signal Process., 2016)

A deep-learning approach to translate between brain structure and functional connectivity. - Vince D. Calhoun; Md Faijul Amin; R. Devon Hjelm; Eswar Damaraju; Sergey M. Plis (ICASSP, 2017)

Decentralized independent vector analysis. - Nikolas P. Wojtalewicz; Rogers F. Silva; Vince D. Calhoun; Anand D. Sarwate; Sergey M. Plis (ICASSP, 2017)

See without looking: joint visualization of sensitive multi-site datasets. - Debbrata K. Saha; Vince D. Calhoun; Sandeep R. Panta; Sergey M. Plis (IJCAI, 2017)

End-to-end learning of brain tissue segmentation from imperfect labeling. - Alex Fedorov; Jeremy Johnson; Eswar Damaraju; Alexei Ozerin; Vince D. Calhoun; Sergey M. Plis (IJCNN, 2017)

Cooperative learning: Decentralized data neural network. - Noah Lewis; Sergey M. Plis; Vince D. Calhoun (IJCNN, 2017)

Discriminating schizophrenia from normal controls using resting state functional network connectivity: A deep neural network and layer-wise relevance propagation method. - Weizheng Yan; Sergey M. Plis; Vince D. Calhoun; Shengfeng Liu; Rongtao Jiang; Tian-Zi Jiang; Jing Sui (MLSP, 2017)

Almost instant brain atlas segmentation for large-scale studies. - Alex Fedorov; Eswar Damaraju; Vince D. Calhoun; Sergey M. Plis (CoRR, 2017)

COINSTAC: Decentralizing the future of brain imaging analysis. - Jing Ming; Eric Verner; Anand D. Sarwate; Ross Kelly; Cory Reed; Torran Kahleck; Rogers F. Silva; Sandeep R. Panta; Jessica A. Turner; Sergey M. Plis; Vince D. Calhoun (F1000Research, 2017)

A constraint optimization approach to causal discovery from subsampled time series data. - Antti Hyttinen; Sergey M. Plis; Matti Järvisalo; Frederick Eberhardt; David Danks (Int. J. Approx. Reason., 2017)

Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. - Mohammad R. Arbabshirani; Sergey M. Plis; Jing Sui; Vince D. Calhoun (NeuroImage, 2017)

Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks. - Hojin Jang; Sergey M. Plis; Vince D. Calhoun; Jong-Hwan Lee (NeuroImage, 2017)

Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation. - Mikhail Pavlov; Sergey Kolesnikov; Sergey M. Plis (AAAI Spring Symposia, 2018)

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. - Lukasz Kidzinski; Sharada Prasanna Mohanty; Carmichael F. Ong; Zhewei Huang; Shuchang Zhou 001; Anton Pechenko; Adam Stelmaszczyk; Piotr Jarosik; Mikhail Pavlov; Sergey Kolesnikov; Sergey M. Plis; Zhibo Chen 001; et al. (CoRR, 2018)

Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR. - Alvaro Ulloa; Sergey M. Plis; Vince D. Calhoun (CoRR, 2018)

Decentralized Analysis of Brain Imaging Data: Voxel-Based Morphometry and Dynamic Functional Network Connectivity. - Harshvardhan Gazula; Bradley T. Baker; Eswar Damaraju; Sergey M. Plis; Sandeep R. Panta; Rogers F. Silva; Vince D. Calhoun (Frontiers Neuroinformatics, 2018)

Reading the (functional) writing on the (structural) wall: Multimodal fusion of brain structure and function via a deep neural network based translation approach reveals novel impairments in schizophrenia. - Sergey M. Plis; Md Faijul Amin; Adam Chekroud; R. Devon Hjelm; Eswar Damaraju; Hyo Jong Lee; Juan R. Bustillo; KyungHyun Cho; Godfrey D. Pearlson; Vince D. Calhoun (NeuroImage, 2018)

Prediction of Progression to Alzheimer's disease with Deep InfoMax. - Alex Fedorov; R. Devon Hjelm; Anees Abrol; Zening Fu; Yuhui Du; Sergey M. Plis; Vince D. Calhoun (BHI, 2019)

Classification As a Criterion to Select Model Order For Dynamic Functional Connectivity States in Rest-fMRI Data. - Debbrata K. Saha; Anees Abrol; Eswar Damaraju; Barnaly Rashid; Sergey M. Plis; Vince D. Calhoun (ISBI, 2019)

Improved Differentially Private Decentralized Source Separation for fMRI Data. - Hafiz Imtiaz; Jafar Mohammadi; Rogers F. Silva; Bradley T. Baker; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (CoRR, 2019)

Transfer Learning of fMRI Dynamics. - Usman Mahmood; Md Mahfuzur Rahman; Alex Fedorov; Zening Fu; Sergey M. Plis (CoRR, 2019)

Learnt dynamics generalizes across tasks, datasets, and populations. - Usman Mahmood; Md Mahfuzur Rahman; Alex Fedorov; Zening Fu; Vince D. Calhoun; Sergey M. Plis (CoRR, 2019)

Grouped sparse projection. - Nicolas Gillis; Riyasat Ohib; Sergey M. Plis; Vamsi K. Potluru (CoRR, 2019)

Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings. - Bradley T. Baker; Anees Abrol; Rogers F. Silva; Eswar Damaraju; Anand D. Sarwate; Vince D. Calhoun; Sergey M. Plis (NeuroImage, 2019)

Amalgamating evidence of dynamics. - David Danks; Sergey M. Plis (Synth., 2019)

Time-varying Graphs: A Method to Identify Abnormal Integration and Disconnection in Functional Brain Connectivity with Application to Schizophrenia. - 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; Armin Iraji; et al. (BIBE, 2020)

Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations. - Usman Mahmood; Md Mahfuzur Rahman; Alex Fedorov; Noah Lewis; Zening Fu; Vince D. Calhoun; Sergey M. Plis (MICCAI (7), 2020)

On self-supervised multi-modal representation learning: An application to Alzheimer's disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (CoRR, 2020)

Taxonomy of multimodal self-supervised representation learning. - Alex Fedorov; Tristan Sylvain; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (CoRR, 2020)

COINSTAC: Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation. - Harshvardhan Gazula; Ross Kelly; Javier Tomas Romero; Eric Verner; Bradley T. Baker; Rogers F. Silva; Hafiz Imtiaz; Debbrata K. Saha; Rajikha Raja; Jessica A. Turner; Anand D. Sarwate; Sergey M. Plis; et al. (J. Open Source Softw., 2020)

Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia. - Haleh Falakshahi; Victor M. Vergara; Jingyu Liu 001; Daniel H. Mathalon; Judith M. Ford; James Voyvodic; Bryon A. Mueller; Aysenil Belger; Sarah C. McEwen; Steven G. Potkin; Adrian Preda; Hooman Rokham; et al. (IEEE Trans. Biomed. Eng., 2020)

Deep learning in resting-state fMRI*. - Anees Abrol; Reihaneh Hassanzadeh; Sergey M. Plis; Vince D. Calhoun (EMBC, 2021)

Fusing multimodal neuroimaging data with a variational autoencoder. - Eloy Geenjaar; Noah Lewis; Zening Fu; Rohan Venkatdas; Sergey M. Plis; Vince D. Calhoun (EMBC, 2021)

Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. - Alex Fedorov; Tristan Sylvain; Eloy Geenjaar; Margaux Luck; Lei Wu 013; Thomas P. DeRamus; Alex Kirilin; Dmitry Bleklov; Vince D. Calhoun; Sergey M. Plis (ICHI, 2021)

Can recurrent models know more than we do? - Noah Lewis; Robyn L. Miller; Harshvardhan Gazula; Md Mahfuzur Rahman; Armin Iraji; Vince D. Calhoun; Sergey M. Plis (ICHI, 2021)

On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. - Alex Fedorov; Lei Wu 013; Tristan Sylvain; Margaux Luck; Thomas P. DeRamus; Dmitry Bleklov; Sergey M. Plis; Vince D. Calhoun (ISBI, 2021)

3-way Parallel Fusion of Spatial (sMRI/dMRI) and Spatio-temporal (fMRI) Data with Application to Schizophrenia. - Shile Qi; Sergey M. Plis; Robyn L. Miller; Rogers F. Silva; Victor M. Vergara; Rongtao Jiang; Dongmei Zhi; Jing Sui; Vince D. Calhoun (ISBI, 2021)

Statelets: A Novel Multi-Dimensional State-Shape Representation Of Brain Functional Connectivity Dynamics. - Md Abdur Rahaman; Eswar Damaraju; Debbrata Kumar Saha; Vince D. Calhoun; Sergey M. Plis (ISBI, 2021)

A Deep Learning Model for Data-Driven Discovery of Functional Connectivity. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (Algorithms, 2021)

A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States. - Debbrata K. Saha; Eswar Damaraju; Barnaly Rashid; Anees Abrol; Sergey M. Plis; Vince D. Calhoun (Brain Connect., 2021)

Efficient Distributed Auto-Differentiation. - Bradley T. Baker; Vince D. Calhoun; Barak A. Pearlmutter; Sergey M. Plis (CoRR, 2021)

Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Thomas P. DeRamus; Vince D. Calhoun; Sergey M. Plis (CoRR, 2021)

Algorithm-Agnostic Explainability for Unsupervised Clustering. - Charles A. Ellis; Mohammad S. Eslampanah Sendi; Sergey M. Plis; Robyn L. Miller; Vince D. Calhoun (CoRR, 2021)

Brain dynamics via Cumulative Auto-Regressive Self-Attention. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (CoRR, 2021)

Multi network InfoMax: A pre-training method involving graph convolutional networks. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (CoRR, 2021)

Single-Shot Pruning for Offline Reinforcement Learning. - Samin Yeasar Arnob; Riyasat Ohib; Sergey M. Plis; Doina Precup (CoRR, 2021)

Decentralized Multisite VBM Analysis During Adolescence Shows Structural Changes Linked to Age, Body Mass Index, and Smoking: a COINSTAC Analysis. - Harshvardhan Gazula; Bharath Holla; Zuo Zhang; Jiayuan Xu; Eric Verner; Ross Kelly; Sanjeev Jain; Rose Dawn Bharath; Gareth J. Barker; Debasish Basu; Amit Chakrabarti; Kartik Kalyanram; et al. (Neuroinformatics, 2021)

Multidataset Independent Subspace Analysis With Application to Multimodal Fusion. - Rogers F. Silva; Sergey M. Plis; Tülay Adali; Marios S. Pattichis; Vince D. Calhoun (IEEE Trans. Image Process., 2021)

A Correlated Noise-Assisted Decentralized Differentially Private Estimation Protocol, and its Application to fMRI Source Separation. - Hafiz Imtiaz; Jafar Mohammadi; Rogers F. Silva; Bradley T. Baker; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (IEEE Trans. Signal Process., 2021)

Mind the gap: functional network connectivity interpolation between schizophrenia patients and controls using a variational autoencoder. - Xinhui Li; Eloy Geenjaar; Zening Fu; Sergey M. Plis; Vince D. Calhoun (EMBC, 2022)

Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (IJCNN, 2022)

Refacing Defaced MRI with PixelCNN. - Yaorong Xiao; William Ashbee; Vince D. Calhoun; Sergey M. Plis (IJCNN, 2022)

Constraint-Based Causal Structure Learning from Undersampled Graphs. - Mohammadsajad Abavisani; David Danks; Sergey M. Plis (CoRR, 2022)

Geometrically Guided Integrated Gradients. - Md Mahfuzur Rahman; Noah Lewis; Sergey M. Plis (CoRR, 2022)

Pipeline-Invariant Representation Learning for Neuroimaging. - Xinhui Li; Alex Fedorov; Mrinal Mathur; Anees Abrol; Gregory Kiar; Sergey M. Plis; Vince D. Calhoun (CoRR, 2022)

Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (CoRR, 2022)

Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI. - Usman Mahmood; Zening Fu; Satrajit S. Ghosh; Vince D. Calhoun; Sergey M. Plis (NeuroImage, 2022)

Decentralized Brain Age Estimation Using MRI Data. - Sunitha Basodi; Rajikha Raja; Bhaskar Ray; Harshvardhan Gazula; Anand D. Sarwate; Sergey M. Plis; Jingyu Liu 001; Eric Verner; Vince D. Calhoun (Neuroinformatics, 2022)

Federated Analysis of Neuroimaging Data: A Review of the Field. - Kelly Rootes-Murdy; Harshvardhan Gazula; Eric Verner; Ross Kelly; Thomas DeRamus; Sergey M. Plis; Anand D. Sarwate; Jessica A. Turner; Vince D. Calhoun (Neuroinformatics, 2022)

NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data. - Nipuna Senanayake; Robert Podschwadt; Daniel Takabi; Vince D. Calhoun; Sergey M. Plis (Neuroinformatics, 2022)

Deep Learning in Neuroimaging: Promises and challenges. - Weizheng Yan; Gang Qu 002; Wenxing Hu; Anees Abrol; Biao Cai; Chen Qiao; Sergey M. Plis; Yu-Ping Wang 002; Jing Sui; Vince D. Calhoun (IEEE Signal Process. Mag., 2022)

Explicit Group Sparse Projection with Applications to Deep Learning and NMF. - Riyasat Ohib; Nicolas Gillis; Niccolò Dalmasso; Sameena Shah; Vamsi K. Potluru; Sergey M. Plis (Trans. Mach. Learn. Res., 2022)

Causal Learning through Deliberate Undersampling. - Kseniya Solovyeva; David Danks; Mohammadsajad Abavisani; Sergey M. Plis (CLeaR, 2023)

Glacier: Glass-Box Transformer for Interpretable Dynamic Neuroimaging. - Usman Mahmood; Zening Fu; Vince D. Calhoun; Sergey M. Plis (ICASSP, 2023)

GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints. - Mohammadsajad Abavisani; David Danks; Sergey M. Plis (ICLR, 2023)

Self-Supervised Mental Disorder Classifiers via Time Reversal. - Zafar Iqbal; Usman Mahmood; Zening Fu; Sergey M. Plis (IJCNN, 2023)

SalientGrads: Sparse Models for Communication Efficient and Data Aware Distributed Federated Training. - Riyasat Ohib; Bishal Thapaliya; Pratyush Gaggenapalli; Jingyu Liu 001; Vince D. Calhoun; Sergey M. Plis (CoRR, 2023)

Learning low-dimensional dynamics from whole-brain data improves task capture. - Eloy Geenjaar; Donghyun Kim; Riyasat Ohib; Marlena Duda; Amrit Kashyap; Sergey M. Plis; Vince D. Calhoun (CoRR, 2023)

Looking deeper into interpretable deep learning in neuroimaging: a comprehensive survey. - Md. Mahfuzur Rahman; Vince D. Calhoun; Sergey M. Plis (CoRR, 2023)

Brainchop: Next Generation Web-Based Neuroimaging Application. - Mohamed Masoud; Pratyush Reddy; Farfalla Hu; Sergey M. Plis (CoRR, 2023)

DynaLay: An Introspective Approach to Dynamic Layer Selection for Deep Networks. - Mrinal Mathur; Sergey M. Plis (CoRR, 2023)

Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility. - Dylan Martin; Sunitha Basodi; Sandeep R. Panta; Kelly Rootes-Murdy; Paul Prae; Anand D. Sarwate; Ross Kelly; Javier Tomas Romero; Bradley T. Baker; Harshvardhan Gazula; Henry Jeremy Bockholt; Jessica A. Turner; et al. (Frontiers Neuroinformatics, 2023)

Brainchop: In-browser MRI volumetric segmentation and rendering. - Mohamed Masoud; Farfalla Hu; Sergey M. Plis (J. Open Source Softw., 2023)

Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains. - Harshvardhan Gazula; Kelly Rootes-Murdy; Bharath Holla; Sunitha Basodi; Zuo Zhang; Eric Verner; Ross Kelly; Pratima Murthy; Amit Chakrabarti; Debasish Basu; Subodh Bhagyalakshmi Nanjayya; Rajkumar Lenin Singh; et al. (Neuroinformatics, 2023)

Advanced machine learning in neuroimaging studies via federated learning. - Sunitha Basodi; Javier Tomas Romero; Sandeep R. Panta; Dylan Martin; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (IEEE Big Data, 2024)

Federated Privacy-Preserving Visualization: A Vision Paper. - Ye Tao; Anand D. Sarwate; Sandeep R. Panta; Sergey M. Plis; Vince D. Calhoun (IEEE Big Data, 2024)

Spatiotemporal Vision Transformer for Weakly Supervised Dense Prediction of Dynamic Brain Maps. - Behnam Kazemivash; Armin Iraji; Sergey M. Plis; Vince D. Calhoun (BMVC, 2024)

Copula linked parallel ICA jointly estimates linked structural and functional MRI brain networks. - Oktay Agcaoglu; Deniz Alaçam; Tülay Adali; Vince D. Calhoun; Rogers F. Silva; Sergey M. Plis; Biozid Bostami (EMBC, 2024)

Classification of Schizophrenia using Intrinsic Connectivity Networks and Incremental Boosting Convolution Neural Networks. - Duc My Vo; Sergey M. Plis; Vince D. Calhoun (EMBC, 2024)

Brainchop: Advancing the Frontier of Web-Based Neuroimaging. - Mohamed Masoud; Pratyush Reddy; Farfalla Hu; Sergey M. Plis (ISBI, 2024)

Privacy-Preserving Visualization of Brain Functional Network Connectivity. - Ye Tao; Anand D. Sarwate; Sandeep R. Panta; Sergey M. Plis; Vince D. Calhoun (ISBI, 2024)

Efficient Reinforcement Learning by Discovering Neural Pathways. - Samin Yeasar Arnob; Riyasat Ohib; Sergey M. Plis; Amy Zhang 001; Alessandro Sordoni; Doina Precup (NeurIPS, 2024)

Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse. - Bradley T. Baker; Barak A. Pearlmutter; Robyn L. Miller; Vince D. Calhoun; Sergey M. Plis (CoRR, 2024)

Unmasking Efficiency: Learning Salient Sparse Models in Non-IID Federated Learning. - Riyasat Ohib; Bishal Thapaliya; Gintare Karolina Dziugaite; Jingyu Liu 001; Vince D. Calhoun; Sergey M. Plis (CoRR, 2024)

Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging. - Bradley T. Baker; Vince D. Calhoun; Sergey M. Plis (CoRR, 2024)

Copula-Linked Parallel ICA: A Method for Coupling Structural and Functional MRI brain Networks. - Oktay Agcaoglu; Rogers F. Silva; Deniz Alaçam; Sergey M. Plis; Tülay Adali; Vince D. Calhoun (CoRR, 2024)

ION-C: Integration of Overlapping Networks via Constraints. - Praveen Nair; Payal Bhandari; Mohammadsajad Abavisani; Sergey M. Plis; David Danks (CoRR, 2024)

Efficient federated learning for distributed neuroimaging data. - Bishal Thapaliya; Riyasat Ohib; Eloy Geenjaar; Jingyu Liu 001; Vince D. Calhoun; Sergey M. Plis (Frontiers Neuroinformatics, 2024)

A simple but tough-to-beat baseline for fMRI time-series classification. - Pavel Popov; Usman Mahmood; Zening Fu; Carl Yang 001; Vince D. Calhoun; Sergey M. Plis (NeuroImage, 2024)

Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC. - 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; et al. (Patterns, 2024)

Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. - Alex Fedorov; Eloy Geenjaar; Lei Wu 013; Tristan Sylvain; Thomas P. DeRamus; Margaux Luck; Maria B. Misiura; Girish Mittapalle; R. Devon Hjelm; Sergey M. Plis; Vince D. Calhoun (NeuroImage, 2024)

HistoJS: Web-Based Analytical Tool for Advancing Multiplexed Images. - Mohamed Masoud; David A. Gutman; Sergey M. Plis (J. Open Source Softw., 2024)

COINSTAC: Decentralizing the future of brain imaging analysis. - Vince D. Calhoun; Sergey M. Plis; Jessica A. Turner; Anand D. Sarwate (Zenodo, 2024)

MIND over Body: Adaptive Thinking using Dynamic Computation. - Mrinal Mathur; Barak A. Pearlmutter; Sergey M. Plis (ICLR, 2025)

Predictive Modeling of Mood Using Functional Network Connectivity: Differential Impacts in Exercise + Smart and Control Groups. - Meenu Ajith; Dawn M. Aycock; Erin B. Tone; Jingyu Liu 001; Maria B. Misiura; Rebecca Ellis; Sergey M. Plis; Tricia Z. King; Vonetta M. Dotson; Vince D. Calhoun (ISBI, 2025)

Federated Analysis of Neuroimaging Data Using Coinstac. - Sunitha Basodi; Ross Kelly; Javier Tomas Romero; Dylan Martin; Sandeep R. Panta; Sergey M. Plis; Anand D. Sarwate; Vince D. Calhoun (ISBI, 2025)

State-of-the-Art Stroke Lesion Segmentation at 1/1000th of Parameters. - Alex Fedorov; Yutong Bu; Xiao Hu 002; Chris Rorden; Sergey M. Plis (ISBI, 2025)

Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help? - Keqi Han; Yao Su 003; Lifang He 001; Liang Zhan; Sergey M. Plis; Vince D. Calhoun; Carl Yang 001 (CoRR, 2025)

Scaling Synthetic Brain Data Generation. - Mike Doan; Sergey M. Plis (IEEE J. Biomed. Health Informatics, 2025)

Guidelines For The Choice Of The Baseline in XAI Attribution Methods. - Cristian Morasso; Giorgio Dolci; Ilaria Boscolo Galazzo; Sergey M. Plis; Gloria Menegaz (CoRR, 2025)

Causal Graph Recovery in Neuroimaging through Answer Set Programming. - Mohammadsajad Abavisani; Kseniya Solovyeva; David Danks; Vince D. Calhoun; Sergey M. Plis (CoRR, 2025)

MindGrab for BrainChop: Fast and Accurate Skull Stripping for Command Line and Browser. - Armina Fani; Mike Doan; Isabelle Le; Alex Fedorov; Malte Hoffmann; Chris Rorden; Sergey M. Plis (CoRR, 2025)

Change of Thought: Adaptive Test-Time Computation. - Mrinal Mathur; Mike Doan; Barak A. Pearlmutter; Sergey M. Plis (CoRR, 2025)