Sergey M. Plis

155 papers A* 6A 4B 9C 1Misc 5Journal 96Unranked 34

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Combining fast and slow fMRI sampling rates can enhance predictive power in resting-state data. NeuroImage Joanne Wardell, Kseniya Solovyeva, David Danks, Niko Huotari, Vesa Kiviniemi, Vesa Korhonen, Thomas DeRamus, Godfrey D. Pearlson, Vince D. Calhoun, Sergey M. Plis
2026	J	`jnl`	SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning. Trans. Mach. Learn. Res. Riyasat Ohib, Bishal Thapaliya, Gintare Karolina Dziugaite, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis
2025	J	`jnl`	Causal Graph Recovery in Neuroimaging through Answer Set Programming. CoRR Mohammadsajad Abavisani, Kseniya Solovyeva, David Danks, Vince D. Calhoun, Sergey M. Plis
2025	J	`jnl`	Change of Thought: Adaptive Test-Time Computation. CoRR Mrinal Mathur, Mike Doan, Barak A. Pearlmutter, Sergey M. Plis
2025	—	`conf`	DECIFRA: Deep Extraction of Causally Informed Features via Restricted Architecture. MLSP Pavel Popov, Cristian Morasso, Giorgio Dolci, Ilaria Boscolo Galazzo, Godfrey D. Pearlson, David Danks, Vince D. Calhoun, Gloria Menegaz, Sergey M. Plis
2025	—	`conf`	Federated Analysis of Neuroimaging Data Using Coinstac. ISBI Sunitha Basodi, Ross Kelly, Javier Tomas Romero, Dylan Martin, Sandeep R. Panta, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun
2025	J	`jnl`	Guidelines For The Choice Of The Baseline in XAI Attribution Methods. CoRR Cristian Morasso, Giorgio Dolci, Ilaria Boscolo Galazzo, Sergey M. Plis, Gloria Menegaz
2025	J	`jnl`	Learning ECG Representations via Poly-Window Contrastive Learning. CoRR Yi Yuan, Joseph Van Duyn, Runze Yan, Zhuoyi Huang, Sulaiman Vesal, Sergey M. Plis, Xiao Hu, Gloria Hyunjung Kwak, Ran Xiao, Alex Fedorov
2025	A*	`conf`	MIND over Body: Adaptive Thinking using Dynamic Computation. ICLR Mrinal Mathur, Barak A. Pearlmutter, Sergey M. Plis
2025	J	`jnl`	MindGrab for BrainChop: Fast and Accurate Skull Stripping for Command Line and Browser. CoRR Armina Fani, Mike Doan, Isabelle Le, Alex Fedorov, Malte Hoffmann, Chris Rorden, Sergey M. Plis
2025	—	`conf`	Predictive Modeling of Mood Using Functional Network Connectivity: Differential Impacts in Exercise + Smart and Control Groups. ISBI Meenu Ajith, Dawn M. Aycock, Erin B. Tone, Jingyu Liu, Maria B. Misiura, Rebecca Ellis, Sergey M. Plis, Tricia Z. King, Vonetta M. Dotson, Vince D. Calhoun
2025	J	`jnl`	Rethinking Functional Brain Connectome Analysis: Do Graph Deep Learning Models Help? CoRR Keqi Han, Yao Su, Lifang He, Liang Zhan, Sergey M. Plis, Vince D. Calhoun, Carl Yang
2025	J	`jnl`	Scaling Synthetic Brain Data Generation. IEEE J. Biomed. Health Informatics Mike Doan, Sergey M. Plis
2025	—	`conf`	State-of-the-Art Stroke Lesion Segmentation at 1/1000th of Parameters. ISBI Alex Fedorov, Yutong Bu, Xiao Hu, Chris Rorden, Sergey M. Plis
2025	J	`jnl`	State-of-the-Art Stroke Lesion Segmentation at 1/1000th of Parameters. CoRR Alex Fedorov, Yutong Bu, Xiao Hu, Chris Rorden, Sergey M. Plis
2025	J	`jnl`	The Marriage of Neurotechnologies and Artificial Intelligence: Ethical, regulatory, and technological aspects. IEEE Signal Process. Mag. Carlo Chiurco, Andrea Favaro, Silvia Francesca Storti, Lorenza Brusini, Ahmed M. Salih, Ilaria Boscolo Galazzo, Sergey M. Plis, Gloria Menegaz
2024	J	`jnl`	A simple but tough-to-beat baseline for fMRI time-series classification. NeuroImage Pavel Popov, Usman Mahmood, Zening Fu, Carl Yang, Vince D. Calhoun, Sergey M. Plis
2024	B	`conf`	Advanced machine learning in neuroimaging studies via federated learning. IEEE Big Data Sunitha Basodi, Javier Tomas Romero, Sandeep R. Panta, Dylan Martin, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun
2024	—	`conf`	Brainchop: Advancing the Frontier of Web-Based Neuroimaging. ISBI Mohamed Masoud, Pratyush Reddy, Farfalla Hu, Sergey M. Plis
2024	—	`conf`	Classification of Schizophrenia using Intrinsic Connectivity Networks and Incremental Boosting Convolution Neural Networks. EMBC Duc My Vo, Sergey M. Plis, Vince D. Calhoun
2024	—	`conf`	Copula linked parallel ICA jointly estimates linked structural and functional MRI brain networks. EMBC Oktay Agcaoglu, Deniz Alaçam, Tülay Adali, Vince D. Calhoun, Rogers F. Silva, Sergey M. Plis, Biozid Bostami
2024	J	`jnl`	Copula-Linked Parallel ICA: A Method for Coupling Structural and Functional MRI brain Networks. CoRR Oktay Agcaoglu, Rogers F. Silva, Deniz Alaçam, Sergey M. Plis, Tülay Adali, Vince D. Calhoun
2024	J	`jnl`	Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC. Patterns 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
2024	A*	`conf`	Efficient Reinforcement Learning by Discovering Neural Pathways. NeurIPS Samin Yeasar Arnob, Riyasat Ohib, Sergey M. Plis, Amy Zhang, Alessandro Sordoni, Doina Precup
2024	J	`jnl`	Efficient federated learning for distributed neuroimaging data. Frontiers Neuroinformatics Bishal Thapaliya, Riyasat Ohib, Eloy Geenjaar, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis
2024	B	`conf`	Federated Privacy-Preserving Visualization: A Vision Paper. IEEE Big Data Ye Tao, Anand D. Sarwate, Sandeep R. Panta, Sergey M. Plis, Vince D. Calhoun
2024	J	`jnl`	HistoJS: Web-Based Analytical Tool for Advancing Multiplexed Images. J. Open Source Softw. Mohamed Masoud, David A. Gutman, Sergey M. Plis
2024	J	`jnl`	ION-C: Integration of Overlapping Networks via Constraints. CoRR Praveen Nair, Payal Bhandari, Mohammadsajad Abavisani, Sergey M. Plis, David Danks
2024	J	`jnl`	Low-Rank Learning by Design: the Role of Network Architecture and Activation Linearity in Gradient Rank Collapse. CoRR Bradley T. Baker, Barak A. Pearlmutter, Robyn L. Miller, Vince D. Calhoun, Sergey M. Plis
2024	—	`conf`	Privacy-Preserving Visualization of Brain Functional Network Connectivity. ISBI Ye Tao, Anand D. Sarwate, Sandeep R. Panta, Sergey M. Plis, Vince D. Calhoun
2024	J	`jnl`	Self-supervised multimodal learning for group inferences from MRI data: Discovering disorder-relevant brain regions and multimodal links. NeuroImage 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
2024	A	`conf`	Spatiotemporal Vision Transformer for Weakly Supervised Dense Prediction of Dynamic Brain Maps. BMVC Behnam Kazemivash, Armin Iraji, Sergey M. Plis, Vince D. Calhoun
2024	J	`jnl`	Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging. CoRR Bradley T. Baker, Vince D. Calhoun, Sergey M. Plis
2024	J	`jnl`	Unmasking Efficiency: Learning Salient Sparse Models in Non-IID Federated Learning. CoRR Riyasat Ohib, Bishal Thapaliya, Gintare Karolina Dziugaite, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis
2023	J	`jnl`	Brainchop: In-browser MRI volumetric segmentation and rendering. J. Open Source Softw. Mohamed Masoud, Farfalla Hu, Sergey M. Plis
2023	J	`jnl`	Brainchop: Next Generation Web-Based Neuroimaging Application. CoRR Mohamed Masoud, Pratyush Reddy, Farfalla Hu, Sergey M. Plis
2023	—	`conf`	Causal Learning through Deliberate Undersampling. CLeaR Kseniya Solovyeva, David Danks, Mohammadsajad Abavisani, Sergey M. Plis
2023	J	`jnl`	DynaLay: An Introspective Approach to Dynamic Layer Selection for Deep Networks. CoRR Mrinal Mathur, Sergey M. Plis
2023	J	`jnl`	Enhancing collaborative neuroimaging research: introducing COINSTAC Vaults for federated analysis and reproducibility. Frontiers Neuroinformatics 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, Nathalia Bianchini Esper, Alexandre R. Franco, Sergey M. Plis, Vince D. Calhoun
2023	J	`jnl`	Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains. Neuroinformatics 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, Roshan Lourembam Singh, Kartik Kalyanram, Kamakshi Kartik, Kalyanaraman Kumaran, Krishnaveni Ghattu, Rebecca Kuriyan, Sunita Simon Kurpad, Gareth J. Barker, Rose Dawn Bharath, Sylvane Desrivières, Meera Purushottam, Dimitri Papadopoulos-Orfanos, Eesha Sharma, Matthew Hickman, Mireille Toledano, Nilakshi Vaidya, Tobias Banaschewski, Arun L. W. Bokde, Herta Flor, Antoine Grigis, Hugh Garavan, Penny A. Gowland, Andreas Heinz, Rüdiger Brühl, Jean-Luc Martinot, Marie-Laure Paillère-Martinot, Eric Artiges, Frauke Nees, Tomás Paus, Luise Poustka, Juliane H. Fröhner, Lauren Robinson, Michael N. Smolka, Henrik Walter, Jeanne Winterer, Robert Whelan, Jessica A. Turner, Anand D. Sarwate, Sergey M. Plis, Vivek Benegal, Gunter Schumann, Vince D. Calhoun
2023	A*	`conf`	GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints. ICLR Mohammadsajad Abavisani, David Danks, Sergey M. Plis
2023	Misc	`conf`	Glacier: Glass-Box Transformer for Interpretable Dynamic Neuroimaging. ICASSP Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2023	J	`jnl`	Learning low-dimensional dynamics from whole-brain data improves task capture. CoRR Eloy Geenjaar, Donghyun Kim, Riyasat Ohib, Marlena Duda, Amrit Kashyap, Sergey M. Plis, Vince D. Calhoun
2023	J	`jnl`	Looking deeper into interpretable deep learning in neuroimaging: a comprehensive survey. CoRR Md. Mahfuzur Rahman, Vince D. Calhoun, Sergey M. Plis
2023	J	`jnl`	SalientGrads: Sparse Models for Communication Efficient and Data Aware Distributed Federated Training. CoRR Riyasat Ohib, Bishal Thapaliya, Pratyush Gaggenapalli, Jingyu Liu, Vince D. Calhoun, Sergey M. Plis
2023	B	`conf`	Self-Supervised Mental Disorder Classifiers via Time Reversal. IJCNN Zafar Iqbal, Usman Mahmood, Zening Fu, Sergey M. Plis
2022	J	`jnl`	Constraint-Based Causal Structure Learning from Undersampled Graphs. CoRR Mohammadsajad Abavisani, David Danks, Sergey M. Plis
2022	J	`jnl`	Decentralized Brain Age Estimation Using MRI Data. Neuroinformatics Sunitha Basodi, Rajikha Raja, Bhaskar Ray, Harshvardhan Gazula, Anand D. Sarwate, Sergey M. Plis, Jingyu Liu, Eric Verner, Vince D. Calhoun
2022	B	`conf`	Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. IJCNN Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2022	J	`jnl`	Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. CoRR Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2022	J	`jnl`	Deep Learning in Neuroimaging: Promises and challenges. IEEE Signal Process. Mag. Weizheng Yan, Gang Qu, Wenxing Hu, Anees Abrol, Biao Cai, Chen Qiao, Sergey M. Plis, Yu-Ping Wang, Jing Sui, Vince D. Calhoun
2022	J	`jnl`	Explicit Group Sparse Projection with Applications to Deep Learning and NMF. Trans. Mach. Learn. Res. Riyasat Ohib, Nicolas Gillis, Niccolò Dalmasso, Sameena Shah, Vamsi K. Potluru, Sergey M. Plis
2022	J	`jnl`	Federated Analysis of Neuroimaging Data: A Review of the Field. Neuroinformatics Kelly Rootes-Murdy, Harshvardhan Gazula, Eric Verner, Ross Kelly, Thomas DeRamus, Sergey M. Plis, Anand D. Sarwate, Jessica A. Turner, Vince D. Calhoun
2022	J	`jnl`	Geometrically Guided Integrated Gradients. CoRR Md Mahfuzur Rahman, Noah Lewis, Sergey M. Plis
2022	—	`conf`	Mind the gap: functional network connectivity interpolation between schizophrenia patients and controls using a variational autoencoder. EMBC Xinhui Li, Eloy Geenjaar, Zening Fu, Sergey M. Plis, Vince D. Calhoun
2022	J	`jnl`	NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data. Neuroinformatics Nipuna Senanayake, Robert Podschwadt, Daniel Takabi, Vince D. Calhoun, Sergey M. Plis
2022	J	`jnl`	Pipeline-Invariant Representation Learning for Neuroimaging. CoRR Xinhui Li, Alex Fedorov, Mrinal Mathur, Anees Abrol, Gregory Kiar, Sergey M. Plis, Vince D. Calhoun
2022	B	`conf`	Refacing Defaced MRI with PixelCNN. IJCNN Yaorong Xiao, William Ashbee, Vince D. Calhoun, Sergey M. Plis
2022	J	`jnl`	Self-Supervised Mental Disorder Classifiers via Time Reversal. CoRR Zafar Iqbal, Usman Mahmood, Zening Fu, Sergey M. Plis
2022	J	`jnl`	Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. CoRR Alex Fedorov, Eloy Geenjaar, Lei Wu, Tristan Sylvain, Thomas P. DeRamus, Margaux Luck, Maria B. Misiura, R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun
2022	J	`jnl`	Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI. NeuroImage Usman Mahmood, Zening Fu, Satrajit S. Ghosh, Vince D. Calhoun, Sergey M. Plis
2021	—	`conf`	3-way Parallel Fusion of Spatial (sMRI/dMRI) and Spatio-temporal (fMRI) Data with Application to Schizophrenia. ISBI Shile Qi, Sergey M. Plis, Robyn L. Miller, Rogers F. Silva, Victor M. Vergara, Rongtao Jiang, Dongmei Zhi, Jing Sui, Vince D. Calhoun
2021	J	`jnl`	A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States. Brain Connect. Debbrata K. Saha, Eswar Damaraju, Barnaly Rashid, Anees Abrol, Sergey M. Plis, Vince D. Calhoun
2021	J	`jnl`	A Correlated Noise-Assisted Decentralized Differentially Private Estimation Protocol, and its Application to fMRI Source Separation. IEEE Trans. Signal Process. Hafiz Imtiaz, Jafar Mohammadi, Rogers F. Silva, Bradley T. Baker, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun
2021	J	`jnl`	A Deep Learning Model for Data-Driven Discovery of Functional Connectivity. Algorithms Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2021	J	`jnl`	A deep learning model for data-driven discovery of functional connectivity. CoRR Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2021	J	`jnl`	Algorithm-Agnostic Explainability for Unsupervised Clustering. CoRR Charles A. Ellis, Mohammad S. Eslampanah Sendi, Sergey M. Plis, Robyn L. Miller, Vince D. Calhoun
2021	J	`jnl`	Brain dynamics via Cumulative Auto-Regressive Self-Attention. CoRR Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2021	—	`conf`	Can recurrent models know more than we do? ICHI Noah Lewis, Robyn L. Miller, Harshvardhan Gazula, Md Mahfuzur Rahman, Armin Iraji, Vince D. Calhoun, Sergey M. Plis
2021	J	`jnl`	Decentralized Multisite VBM Analysis During Adolescence Shows Structural Changes Linked to Age, Body Mass Index, and Smoking: a COINSTAC Analysis. Neuroinformatics 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, Kalyanaraman Kumaran, Rajkumar Lenin Singh, Rebecca Kuriyan, Pratima Murthy, Vivek Benega, Sergey M. Plis, Anand D. Sarwate, Jessica A. Turner, Gunter Schumann, Vince D. Calhoun
2021	—	`conf`	Deep learning in resting-state fMRI EMBC Anees Abrol, Reihaneh Hassanzadeh, Sergey M. Plis, Vince D. Calhoun
2021	J	`jnl`	Efficient Distributed Auto-Differentiation. CoRR Bradley T. Baker, Vince D. Calhoun, Barak A. Pearlmutter, Sergey M. Plis
2021	—	`conf`	Fusing multimodal neuroimaging data with a variational autoencoder. EMBC Eloy Geenjaar, Noah Lewis, Zening Fu, Rohan Venkatdas, Sergey M. Plis, Vince D. Calhoun
2021	J	`jnl`	Fusing multimodal neuroimaging data with a variational autoencoder. CoRR Eloy Geenjaar, Noah Lewis, Zening Fu, Rohan Venkatdas, Sergey M. Plis, Vince D. Calhoun
2021	J	`jnl`	Multi network InfoMax: A pre-training method involving graph convolutional networks. CoRR Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2021	J	`jnl`	Multidataset Independent Subspace Analysis With Application to Multimodal Fusion. IEEE Trans. Image Process. Rogers F. Silva, Sergey M. Plis, Tülay Adali, Marios S. Pattichis, Vince D. Calhoun
2021	—	`conf`	On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. ISBI Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun
2021	—	`conf`	Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. ICHI Alex Fedorov, Tristan Sylvain, Eloy Geenjaar, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis
2021	J	`jnl`	Single-Shot Pruning for Offline Reinforcement Learning. CoRR Samin Yeasar Arnob, Riyasat Ohib, Sergey M. Plis, Doina Precup
2021	—	`conf`	Statelets: A Novel Multi-Dimensional State-Shape Representation Of Brain Functional Connectivity Dynamics. ISBI Md Abdur Rahaman, Eswar Damaraju, Debbrata Kumar Saha, Vince D. Calhoun, Sergey M. Plis
2021	J	`jnl`	Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data. CoRR Alex Fedorov, Eloy Geenjaar, Lei Wu, Thomas P. DeRamus, Vince D. Calhoun, Sergey M. Plis
2020	J	`jnl`	COINSTAC: Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation. J. Open Source Softw. 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, Vince D. Calhoun
2020	J	`jnl`	Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia. IEEE Trans. Biomed. Eng. Haleh Falakshahi, Victor M. Vergara, Jingyu Liu, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah C. McEwen, Steven G. Potkin, Adrian Preda, Hooman Rokham, Jing Sui, Jessica A. Turner, Sergey M. Plis, Vince D. Calhoun
2020	J	`jnl`	Meta-modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia. CoRR Haleh Falakshahi, Victor M. Vergara, Jingyu Liu, Daniel H. Mathalon, Judith M. Ford, James Voyvodic, Bryon A. Mueller, Aysenil Belger, Sarah C. McEwen, Steven G. Potkin, Adrian Preda, Hooman Rokham, Jing Sui, Jessica A. Turner, Sergey M. Plis, Vince D. Calhoun
2020	J	`jnl`	On self-supervised multi-modal representation learning: An application to Alzheimer's disease. CoRR Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun
2020	J	`jnl`	Taxonomy of multimodal self-supervised representation learning. CoRR Alex Fedorov, Tristan Sylvain, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis
2020	C	`conf`	Time-varying Graphs: A Method to Identify Abnormal Integration and Disconnection in Functional Brain Connectivity with Application to Schizophrenia. BIBE 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, Jessica A. Turner, Sergey M. Plis, Vince D. Calhoun
2020	—	`conf`	Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations. MICCAI (7) Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Noah Lewis, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2020	J	`jnl`	Whole MILC: generalizing learned dynamics across tasks, datasets, and populations. CoRR Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Noah Lewis, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2019	J	`jnl`	Amalgamating evidence of dynamics. Synth. David Danks, Sergey M. Plis
2019	—	`conf`	Classification As a Criterion to Select Model Order For Dynamic Functional Connectivity States in Rest-fMRI Data. ISBI Debbrata K. Saha, Anees Abrol, Eswar Damaraju, Barnaly Rashid, Sergey M. Plis, Vince D. Calhoun
2019	J	`jnl`	Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings. NeuroImage Bradley T. Baker, Anees Abrol, Rogers F. Silva, Eswar Damaraju, Anand D. Sarwate, Vince D. Calhoun, Sergey M. Plis
2019	J	`jnl`	Grouped sparse projection. CoRR Nicolas Gillis, Riyasat Ohib, Sergey M. Plis, Vamsi K. Potluru
2019	J	`jnl`	Improved Differentially Private Decentralized Source Separation for fMRI Data. CoRR Hafiz Imtiaz, Jafar Mohammadi, Rogers F. Silva, Bradley T. Baker, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun
2019	J	`jnl`	Learnt dynamics generalizes across tasks, datasets, and populations. CoRR Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Vince D. Calhoun, Sergey M. Plis
2019	J	`jnl`	Multidataset Independent Subspace Analysis with Application to Multimodal Fusion. CoRR Rogers F. Silva, Sergey M. Plis, Tülay Adali, Marios S. Pattichis, Vince D. Calhoun
2019	—	`conf`	Prediction of Progression to Alzheimer's disease with Deep InfoMax. BHI Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun
2019	J	`jnl`	Prediction of Progression to Alzheimer's disease with Deep InfoMax. CoRR Alex Fedorov, R. Devon Hjelm, Anees Abrol, Zening Fu, Yuhui Du, Sergey M. Plis, Vince D. Calhoun
2019	J	`jnl`	Transfer Learning of fMRI Dynamics. CoRR Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Sergey M. Plis
2018	J	`jnl`	Decentralized Analysis of Brain Imaging Data: Voxel-Based Morphometry and Dynamic Functional Network Connectivity. Frontiers Neuroinformatics Harshvardhan Gazula, Bradley T. Baker, Eswar Damaraju, Sergey M. Plis, Sandeep R. Panta, Rogers F. Silva, Vince D. Calhoun
2018	J	`jnl`	Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR. CoRR Alvaro Ulloa, Sergey M. Plis, Vince D. Calhoun
2018	J	`jnl`	Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. CoRR Lukasz Kidzinski, Sharada Prasanna Mohanty, Carmichael F. Ong, Zhewei Huang, Shuchang Zhou, Anton Pechenko, Adam Stelmaszczyk, Piotr Jarosik, Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis, Zhibo Chen, Zhizheng Zhang, Jiale Chen, Jun Shi, Zhuobin Zheng, Chun Yuan, Zhihui Lin, Henryk Michalewski, Piotr Milos, Blazej Osinski, Andrew Melnik, Malte Schilling, Helge J. Ritter, Sean F. Carroll, Jennifer L. Hicks, Sergey Levine, Marcel Salathé, Scott L. Delp
2018	J	`jnl`	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. NeuroImage 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
2018	—	`conf`	Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation. AAAI Spring Symposia Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis
2017	J	`jnl`	A constraint optimization approach to causal discovery from subsampled time series data. Int. J. Approx. Reason. Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
2017	Misc	`conf`	A deep-learning approach to translate between brain structure and functional connectivity. ICASSP Vince D. Calhoun, Md Faijul Amin, R. Devon Hjelm, Eswar Damaraju, Sergey M. Plis
2017	J	`jnl`	Almost instant brain atlas segmentation for large-scale studies. CoRR Alex Fedorov, Eswar Damaraju, Vince D. Calhoun, Sergey M. Plis
2017	J	`jnl`	COINSTAC: Decentralizing the future of brain imaging analysis. F1000Research 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
2017	B	`conf`	Cooperative learning: Decentralized data neural network. IJCNN Noah Lewis, Sergey M. Plis, Vince D. Calhoun
2017	Misc	`conf`	Decentralized independent vector analysis. ICASSP Nikolas P. Wojtalewicz, Rogers F. Silva, Vince D. Calhoun, Anand D. Sarwate, Sergey M. Plis
2017	—	`conf`	Discriminating schizophrenia from normal controls using resting state functional network connectivity: A deep neural network and layer-wise relevance propagation method. MLSP Weizheng Yan, Sergey M. Plis, Vince D. Calhoun, Shengfeng Liu, Rongtao Jiang, Tian-Zi Jiang, Jing Sui
2017	B	`conf`	End-to-end learning of brain tissue segmentation from imperfect labeling. IJCNN Alex Fedorov, Jeremy Johnson, Eswar Damaraju, Alexei Ozerin, Vince D. Calhoun, Sergey M. Plis
2017	J	`jnl`	Run, skeleton, run: skeletal model in a physics-based simulation. CoRR Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis
2017	A*	`conf`	See without looking: joint visualization of sensitive multi-site datasets. IJCAI Debbrata K. Saha, Vince D. Calhoun, Sandeep R. Panta, Sergey M. Plis
2017	J	`jnl`	Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. NeuroImage Mohammad R. Arbabshirani, Sergey M. Plis, Jing Sui, Vince D. Calhoun
2017	J	`jnl`	Task-specific feature extraction and classification of fMRI volumes using a deep neural network initialized with a deep belief network: Evaluation using sensorimotor tasks. NeuroImage Hojin Jang, Sergey M. Plis, Vince D. Calhoun, Jong-Hwan Lee
2016	J	`jnl`	A Tool for Interactive Data Visualization: Application to Over 10, 000 Brain Imaging and Phantom MRI Data Sets. Frontiers Neuroinformatics 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, Vince D. Calhoun
2016	J	`jnl`	Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling. IEEE J. Sel. Top. Signal Process. Rogers F. Silva, Sergey M. Plis, Jing Sui, Marios S. Pattichis, Tülay Adali, Vince D. Calhoun
2016	—	`conf`	Causal Discovery from Subsampled Time Series Data by Constraint Optimization. Probabilistic Graphical Models Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
2016	J	`jnl`	Causal Discovery from Subsampled Time Series Data by Constraint Optimization. CoRR Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
2016	Misc	`conf`	Data-weighted ensemble learning for privacy-preserving distributed learning. ICASSP Liyang Xie, Sergey M. Plis, Anand D. Sarwate
2016	J	`jnl`	End-to-end learning of brain tissue segmentation from imperfect labeling. CoRR Alex Fedorov, Jeremy Johnson, Eswar Damaraju, Alexei Ozerin, Vince D. Calhoun, Sergey M. Plis
2016	—	`conf`	Multimodal fusion of brain structural and functional imaging with a deep neural machine translation approach. SSIAI Md Faijul Amin, Sergey M. Plis, Eswar Damaraju, R. Devon Hjelm, Kyunghyun Cho, Vince D. Calhoun
2016	Misc	`conf`	Privacy-preserving source separation for distributed data using independent component analysis. CISS Hafiz Imtiaz, Rogers F. Silva, Bradley T. Baker, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun
2016	J	`jnl`	Recurrent Neural Networks for Spatiotemporal Dynamics of Intrinsic Networks from fMRI Data. CoRR R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun
2016	J	`jnl`	Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data. CoRR R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun
2015	—	`conf`	Deep independence network analysis of structural brain imaging: A simulation study. MLSP Eduardo Castro, R. Devon Hjelm, Sergey M. Plis, Laurent Dinh, Jessica A. Turner, Vince D. Calhoun
2015	—	`conf`	Generation of synthetic structural magnetic resonance images for deep learning pre-training. ISBI Eduardo Castro, Alvaro Ulloa, Sergey M. Plis, Jessica A. Turner, Vince D. Calhoun
2015	—	`conf`	Large scale collaboration with autonomy: Decentralized data ICA. MLSP Bradley T. Baker, Rogers F. Silva, Vince D. Calhoun, Anand D. Sarwate, Sergey M. Plis
2015	A	`conf`	Mesochronal Structure Learning. UAI Sergey M. Plis, David Danks, Jianyu Yang
2015	—	`conf`	Rate-Agnostic (Causal) Structure Learning. NIPS Sergey M. Plis, David Danks, Cynthia Freeman, Vince D. Calhoun
2015	—	`conf`	Synthetic structural magnetic resonance image generator improves deep learning prediction of schizophrenia. MLSP Alvaro Ulloa, Sergey M. Plis, Erik B. Erhardt, Vince D. Calhoun
2014	J	`jnl`	A statistically motivated framework for simulation of stochastic data fusion models applied to multimodal neuroimaging. NeuroImage Rogers F. Silva, Sergey M. Plis, Tülay Adali, Vince D. Calhoun
2014	—	`conf`	Deep learning for neuroimaging: a validation study. ICLR (Workshop Poster) Sergey M. Plis, R. Devon Hjelm, Ruslan Salakhutdinov, Vince D. Calhoun
2014	J	`jnl`	Functional and effective connectivity of stopping. NeuroImage René J. Huster, Sergey M. Plis, Christina F. Lavallee, Vince D. Calhoun, Christoph S. Herrmann
2014	J	`jnl`	High-order interactions observed in multi-task intrinsic networks are dominant indicators of aberrant brain function in schizophrenia. NeuroImage 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
2014	J	`jnl`	Impact of autocorrelation on functional connectivity. NeuroImage 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
2014	B	`conf`	Multidataset independent subspace analysis extends independent vector analysis. ICIP Rogers F. Silva, Sergey M. Plis, Tülay Adali, Vince D. Calhoun
2014	J	`jnl`	Restricted Boltzmann machines for neuroimaging: An application in identifying intrinsic networks. NeuroImage R. Devon Hjelm, Vince D. Calhoun, Ruslan Salakhutdinov, Elena A. Allen, Tülay Adali, Sergey M. Plis
2014	J	`jnl`	Sharing privacy-sensitive access to neuroimaging and genetics data: a review and preliminary validation. Frontiers Neuroinformatics Anand D. Sarwate, Sergey M. Plis, Jessica A. Turner, Mohammad Arbabshirani, Vince D. Calhoun
2014	—	`conf`	The tenth annual MLSP competition: Schizophrenia classification challenge. MLSP Rogers F. Silva, Eduardo Castro, Cota Navin Gupta, Mustafa S. Çetin, Mohammad Arbabshirani, Vamsi K. Potluru, Sergey M. Plis, Vince D. Calhoun
2013	A*	`conf`	Block Coordinate Descent for Sparse NMF ICLR (Poster) Vamsi K. Potluru, Sergey M. Plis, Jonathan Le Roux, Barak A. Pearlmutter, Vince D. Calhoun, Thomas P. Hayes
2011	J	`jnl`	Correlated Noise: How it Breaks NMF, and What to Do About it. J. Signal Process. Syst. Sergey M. Plis, Vamsi K. Potluru, Terran Lane, Vince D. Calhoun
2011	A	`conf`	Directional Statistics on Permutations. AISTATS Sergey M. Plis, Stephen McCracken, Terran Lane, Vince D. Calhoun
2011	J	`jnl`	Effective connectivity analysis of fMRI and MEG data collected under identical paradigms. Comput. Biol. Medicine Sergey M. Plis, Michael P. Weisend, Eswar Damaraju, Tom Eichele, Andy R. Mayer, Vincent P. Clark, Terran Lane, Vince D. Calhoun
2011	B	`conf`	Sparseness and a reduction from Totally Nonnegative Least Squares to SVM. IJCNN Vamsi K. Potluru, Sergey M. Plis, Shuang Luan, Vince D. Calhoun, Thomas P. Hayes
2010	—	`conf`	Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks. ECML/PKDD (1) Eva Besada-Portas, Sergey M. Plis, Jesús Manuel de la Cruz, Terran Lane
2010	J	`jnl`	MEG and fMRI fusion for nonlinear estimation of neural and BOLD signal changes. Frontiers Neuroinformatics Sergey M. Plis, Vince D. Calhoun, Tom Eichele, Michael P. Weisend, Terran Lane
2010	A*	`conf`	Permutations as Angular Data: Efficient Inference in Factorial Spaces. ICDM Sergey M. Plis, Terran Lane, Vince D. Calhoun
2009	A	`conf`	Efficient Multiplicative Updates for Support Vector Machines. SDM Vamsi K. Potluru, Sergey M. Plis, Morten Mørup, Vincent D. Calhoun, Terran Lane
2009	J	`jnl`	Multiplicative updates For Non-Negative Kernel SVM CoRR Vamsi K. Potluru, Sergey M. Plis, Morten Mørup, Vince D. Calhoun, Terran Lane
2009	—	`conf`	Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks. ECML/PKDD (1) Eva Besada-Portas, Sergey M. Plis, Jesús Manuel de la Cruz, Terran Lane
2008	J	`jnl`	Bayesian brain source imaging based on combined MEG/EEG and fMRI using MCMC. NeuroImage Sung C. Jun, John S. George, Woohan Kim, E. Juliana Paré-Blagoev, Sergey M. Plis, Douglas M. Ranken, David M. Schmidt
2006	—	`conf`	A generalized spatiotemporal covariance model for stationary background in analysis of MEG data. EMBC Sergey M. Plis, David M. Schmidt, Sung C. Jun, Douglas M. Ranken
2005	J	`jnl`	Spatiotemporal Bayesian inference dipole analysis for MEG neuroimaging data. NeuroImage Sung C. Jun, John S. George, E. Juliana Paré-Blagoev, Sergey M. Plis, Douglas M. Ranken, David M. Schmidt, C. C. Wood