Sergey M. Plis

ORCID

Publication Activity (10 Years)

Years Active: 2005-2024
Publications (10 Years): 101

Top Venues

Publications

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)
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)
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)
Mohamed Masoud, David A. Gutman, Sergey M. Plis
HistoJS: Web-Based Analytical Tool for Advancing Multiplexed Images. J. Open Source Softw. 9 (94) (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)
Bradley T. Baker, Vince D. Calhoun, Sergey M. Plis
Spectral Introspection Identifies Group Training Dynamics in Deep Neural Networks for Neuroimaging. CoRR (2024)
Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
Glacier: Glass-Box Transformer for Interpretable Dynamic Neuroimaging. ICASSP (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)
Mrinal Mathur, Sergey M. Plis
DynaLay: An Introspective Approach to Dynamic Layer Selection for Deep Networks. CoRR (2023)
Zafar Iqbal, Usman Mahmood, Zening Fu, Sergey M. Plis
Self-Supervised Mental Disorder Classifiers via Time Reversal. IJCNN (2023)
Mohamed Masoud, Pratyush Reddy, Farfalla Hu, Sergey M. Plis
Brainchop: Next Generation Web-Based Neuroimaging Application. 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)
Mohammadsajad Abavisani, David Danks, Sergey M. Plis
GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints. ICLR (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)
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 Desrivieres, 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 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
Federated Analysis in COINSTAC Reveals Functional Network Connectivity and Spectral Links to Smoking and Alcohol Consumption in Nearly 2,000 Adolescent Brains. Neuroinformatics 21 (2) (2023)
Kseniya Solovyeva, David Danks, Mohammadsajad Abavisani, Sergey M. Plis
Causal Learning through Deliberate Undersampling. CLeaR (2023)
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
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes. CoRR (2022)
Sunitha Basodi, Rajikha Raja, Bhaskar Ray, Harshvardhan Gazula, Anand D. Sarwate, Sergey M. Plis, Jingyu Liu, Eric Verner, Vince D. Calhoun
Decentralized Brain Age Estimation Using MRI Data. Neuroinformatics 20 (4) (2022)
Mohammadsajad Abavisani, David Danks, Sergey M. Plis
Constraint-Based Causal Structure Learning from Undersampled Graphs. CoRR (2022)
Zafar Iqbal, Usman Mahmood, Zening Fu, Sergey M. Plis
Self-Supervised Mental Disorder Classifiers via Time Reversal. CoRR (2022)
Weizheng Yan, Gang Qu, Wenxing Hu, Anees Abrol, Biao Cai, Chen Qiao, Sergey M. Plis, Yu-Ping Wang, Jing Sui, Vince D. Calhoun
Deep Learning in Neuroimaging: Promises and challenges. IEEE Signal Process. Mag. 39 (2) (2022)
Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
Deep Dynamic Effective Connectivity Estimation from Multivariate Time Series. IJCNN (2022)
Riyasat Ohib, Nicolas Gillis, Niccolò Dalmasso, Sameena Shah, Vamsi K. Potluru, Sergey M. Plis
Explicit Group Sparse Projection with Applications to Deep Learning and NMF. Trans. Mach. Learn. Res. 2022 (2022)
Usman Mahmood, Zening Fu, Satrajit S. Ghosh, Vince D. Calhoun, Sergey M. Plis
Through the looking glass: Deep interpretable dynamic directed connectivity in resting fMRI. NeuroImage 264 (2022)
Md Mahfuzur Rahman, Noah Lewis, Sergey M. Plis
Geometrically Guided Integrated Gradients. CoRR (2022)
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)
Kelly Rootes-Murdy, Harshvardhan Gazula, Eric Verner, Ross Kelly, Thomas DeRamus, Sergey M. Plis, Anand D. Sarwate, Jessica A. Turner, Vince D. Calhoun
Federated Analysis of Neuroimaging Data: A Review of the Field. Neuroinformatics 20 (2) (2022)
Nipuna Senanayake, Robert Podschwadt, Daniel Takabi, Vince D. Calhoun, Sergey M. Plis
NeuroCrypt: Machine Learning Over Encrypted Distributed Neuroimaging Data. Neuroinformatics 20 (1) (2022)
Xinhui Li, Alex Fedorov, Mrinal Mathur, Anees Abrol, Gregory Kiar, Sergey M. Plis, Vince D. Calhoun
Pipeline-Invariant Representation Learning for Neuroimaging. CoRR (2022)
Yaorong Xiao, William Ashbee, Vince D. Calhoun, Sergey M. Plis
Refacing Defaced MRI with PixelCNN. IJCNN (2022)
Shile Qi, Sergey M. Plis, Robyn L. Miller, Rogers F. Silva, Victor M. Vergara, Rongtao Jiang, Dongmei Zhi, Jing Sui, Vince D. Calhoun
3-way Parallel Fusion of Spatial (sMRI/dMRI) and Spatio-temporal (fMRI) Data with Application to Schizophrenia. ISBI (2021)
Alex Fedorov, Tristan Sylvain, Eloy Geenjaar, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis
Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease. ICHI (2021)
Eloy Geenjaar, Noah Lewis, Zening Fu, Rohan Venkatdas, Sergey M. Plis, Vince D. Calhoun
Fusing multimodal neuroimaging data with a variational autoencoder. CoRR (2021)
Md Abdur Rahaman, Eswar Damaraju, Debbrata Kumar Saha, Vince D. Calhoun, Sergey M. Plis
Statelets: A Novel Multi-Dimensional State-Shape Representation Of Brain Functional Connectivity Dynamics. ISBI (2021)
Anees Abrol, Reihaneh Hassanzadeh, Sergey M. Plis, Vince D. Calhoun
. EMBC (2021)
Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
Brain dynamics via Cumulative Auto-Regressive Self-Attention. CoRR (2021)
Debbrata K. Saha, Eswar Damaraju, Barnaly Rashid, Anees Abrol, Sergey M. Plis, Vince D. Calhoun
A Classification-Based Approach to Estimate the Number of Resting Functional Magnetic Resonance Imaging Dynamic Functional Connectivity States. Brain Connect. 11 (2) (2021)
Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
A deep learning model for data-driven discovery of functional connectivity. CoRR (2021)
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, Lenin Singh, Rebecca Kuriyan, Pratima Murthy, Vivek Benega, Sergey M. Plis, Anand D. Sarwate, Jessica A. Turner, Gunter Schumann, Vince D. Calhoun
Decentralized Multisite VBM Analysis During Adolescence Shows Structural Changes Linked to Age, Body Mass Index, and Smoking: a COINSTAC Analysis. Neuroinformatics 19 (4) (2021)
Rogers F. Silva, Sergey M. Plis, Tülay Adali, Marios S. Pattichis, Vince D. Calhoun
Multidataset Independent Subspace Analysis With Application to Multimodal Fusion. IEEE Trans. Image Process. 30 (2021)
Samin Yeasar Arnob, Riyasat Ohib, Sergey M. Plis, Doina Precup
Single-Shot Pruning for Offline Reinforcement Learning. CoRR (2021)
Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
Multi network InfoMax: A pre-training method involving graph convolutional networks. CoRR (2021)
Bradley T. Baker, Vince D. Calhoun, Barak A. Pearlmutter, Sergey M. Plis
Efficient Distributed Auto-Differentiation. CoRR (2021)
Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun
On Self-Supervised Multimodal Representation Learning: An Application To Alzheimer's Disease. ISBI (2021)
Noah Lewis, Robyn L. Miller, Harshvardhan Gazula, Md Mahfuzur Rahman, Armin Iraji, Vince D. Calhoun, Sergey M. Plis
Can recurrent models know more than we do? ICHI (2021)
Alex Fedorov, Eloy Geenjaar, Lei Wu, Thomas P. DeRamus, Vince D. Calhoun, Sergey M. Plis
Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI data. CoRR (2021)
Charles A. Ellis, Mohammad S. Eslampanah Sendi, Sergey M. Plis, Robyn L. Miller, Vince D. Calhoun
Algorithm-Agnostic Explainability for Unsupervised Clustering. CoRR (2021)
Usman Mahmood, Zening Fu, Vince D. Calhoun, Sergey M. Plis
A Deep Learning Model for Data-Driven Discovery of Functional Connectivity. Algorithms 14 (3) (2021)
Hafiz Imtiaz, Jafar Mohammadi, Rogers F. Silva, Bradley T. Baker, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun
A Correlated Noise-Assisted Decentralized Differentially Private Estimation Protocol, and its Application to fMRI Source Separation. IEEE Trans. Signal Process. 69 (2021)
Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Noah Lewis, Zening Fu, Vince D. Calhoun, Sergey M. Plis
Whole MILC: generalizing learned dynamics across tasks, datasets, and populations. CoRR (2020)
Alex Fedorov, Tristan Sylvain, Margaux Luck, Lei Wu, Thomas P. DeRamus, Alex Kirilin, Dmitry Bleklov, Vince D. Calhoun, Sergey M. Plis
Taxonomy of multimodal self-supervised representation learning. CoRR (2020)
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
Meta-Modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia. IEEE Trans. Biomed. Eng. 67 (9) (2020)
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
Meta-modal Information Flow: A Method for Capturing Multimodal Modular Disconnectivity in Schizophrenia. CoRR (2020)
Harshvardhan Gazula, Ross Kelly, Javier 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
COINSTAC: Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation. J. Open Source Softw. 5 (54) (2020)
Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Noah Lewis, Zening Fu, Vince D. Calhoun, Sergey M. Plis
Whole MILC: Generalizing Learned Dynamics Across Tasks, Datasets, and Populations. MICCAI (7) (2020)
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
Time-varying Graphs: A Method to Identify Abnormal Integration and Disconnection in Functional Brain Connectivity with Application to Schizophrenia. BIBE (2020)
Alex Fedorov, Lei Wu, Tristan Sylvain, Margaux Luck, Thomas P. DeRamus, Dmitry Bleklov, Sergey M. Plis, Vince D. Calhoun
On self-supervised multi-modal representation learning: An application to Alzheimer's disease. CoRR (2020)
Bradley T. Baker, Anees Abrol, Rogers F. Silva, Eswar Damaraju, Anand D. Sarwate, Vince D. Calhoun, Sergey M. Plis
Decentralized temporal independent component analysis: Leveraging fMRI data in collaborative settings. NeuroImage 186 (2019)
Debbrata K. Saha, Anees Abrol, Eswar Damaraju, Barnaly Rashid, Sergey M. Plis, Vince D. Calhoun
Classification As a Criterion to Select Model Order For Dynamic Functional Connectivity States in Rest-fMRI Data. ISBI (2019)
David Danks, Sergey M. Plis
Amalgamating evidence of dynamics. Synth. 196 (8) (2019)
Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Vince D. Calhoun, Sergey M. Plis
Learnt dynamics generalizes across tasks, datasets, and populations. CoRR (2019)
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. BHI (2019)
Hafiz Imtiaz, Jafar Mohammadi, Rogers F. Silva, Bradley T. Baker, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun
Improved Differentially Private Decentralized Source Separation for fMRI Data. CoRR (2019)
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 (2019)
Rogers F. Silva, Sergey M. Plis, Tülay Adali, Marios S. Pattichis, Vince D. Calhoun
Multidataset Independent Subspace Analysis with Application to Multimodal Fusion. CoRR (2019)
Usman Mahmood, Md Mahfuzur Rahman, Alex Fedorov, Zening Fu, Sergey M. Plis
Transfer Learning of fMRI Dynamics. CoRR (2019)
Nicolas Gillis, Riyasat Ohib, Sergey M. Plis, Vamsi K. Potluru
Grouped sparse projection. CoRR (2019)
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
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 181 (2018)
Alvaro Ulloa, Sergey M. Plis, Vince D. Calhoun
Improving Classification Rate of Schizophrenia Using a Multimodal Multi-Layer Perceptron Model with Structural and Functional MR. CoRR (2018)
Harshvardhan Gazula, Bradley T. Baker, Eswar Damaraju, Sergey M. Plis, Sandeep R. Panta, Rogers F. Silva, Vince D. Calhoun
Decentralized Analysis of Brain Imaging Data: Voxel-Based Morphometry and Dynamic Functional Network Connectivity. Frontiers Neuroinformatics 12 (2018)
Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis
Run, Skeleton, Run: Skeletal Model in a Physics-Based Simulation. AAAI Spring Symposia (2018)
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
Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments. CoRR (2018)
Nikolas P. Wojtalewicz, Rogers F. Silva, Vince D. Calhoun, Anand D. Sarwate, Sergey M. Plis
Decentralized independent vector analysis. ICASSP (2017)
Debbrata K. Saha, Vince D. Calhoun, Sandeep R. Panta, Sergey M. Plis
See without looking: joint visualization of sensitive multi-site datasets. IJCAI (2017)
Hojin Jang, Sergey M. Plis, Vince D. Calhoun, Jong-Hwan Lee
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 145 (2017)
Mikhail Pavlov, Sergey Kolesnikov, Sergey M. Plis
Run, skeleton, run: skeletal model in a physics-based simulation. CoRR (2017)
Alex Fedorov, Eswar Damaraju, Vince D. Calhoun, Sergey M. Plis
Almost instant brain atlas segmentation for large-scale studies. CoRR (2017)
Vince D. Calhoun, Md Faijul Amin, R. Devon Hjelm, Eswar Damaraju, Sergey M. Plis
A deep-learning approach to translate between brain structure and functional connectivity. ICASSP (2017)
Alex Fedorov, Jeremy Johnson, Eswar Damaraju, Alexei Ozerin, Vince D. Calhoun, Sergey M. Plis
End-to-end learning of brain tissue segmentation from imperfect labeling. IJCNN (2017)
Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
A constraint optimization approach to causal discovery from subsampled time series data. Int. J. Approx. Reason. 90 (2017)
Weizheng Yan, Sergey M. Plis, Vince D. Calhoun, Shengfeng Liu, Rongtao Jiang, Tian-Zi Jiang, Jing Sui
Discriminating schizophrenia from normal controls using resting state functional network connectivity: A deep neural network and layer-wise relevance propagation method. MLSP (2017)
Jing Ming, Eric Verner, Anand D. Sarwate, Ross Kelly, Cory Reed, Torran Kahleck, Rogers F. Silva, Sandeep R. Panta, Jessica Turner, Sergey M. Plis, Vince D. Calhoun
COINSTAC: Decentralizing the future of brain imaging analysis. F1000Research 6 (2017)
Noah Lewis, Sergey M. Plis, Vince D. Calhoun
Cooperative learning: Decentralized data neural network. IJCNN (2017)
Mohammad R. Arbabshirani, Sergey M. Plis, Jing Sui, Vince D. Calhoun
Single subject prediction of brain disorders in neuroimaging: Promises and pitfalls. NeuroImage 145 (2017)
Liyang Xie, Sergey M. Plis, Anand D. Sarwate
Data-weighted ensemble learning for privacy-preserving distributed learning. ICASSP (2016)
Md Faijul Amin, Sergey M. Plis, Eswar Damaraju, R. Devon Hjelm, Kyunghyun Cho, Vince D. Calhoun
Multimodal fusion of brain structural and functional imaging with a deep neural machine translation approach. SSIAI (2016)
Alex Fedorov, Jeremy Johnson, Eswar Damaraju, Alexei Ozerin, Vince D. Calhoun, Sergey M. Plis
End-to-end learning of brain tissue segmentation from imperfect labeling. CoRR (2016)
Rogers F. Silva, Sergey M. Plis, Jing Sui, Marios S. Pattichis, Tülay Adali, Vince D. Calhoun
Blind Source Separation for Unimodal and Multimodal Brain Networks: A Unifying Framework for Subspace Modeling. IEEE J. Sel. Top. Signal Process. 10 (7) (2016)
Hafiz Imtiaz, Rogers F. Silva, Bradley T. Baker, Sergey M. Plis, Anand D. Sarwate, Vince D. Calhoun
Privacy-preserving source separation for distributed data using independent component analysis. CISS (2016)
Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
Causal Discovery from Subsampled Time Series Data by Constraint Optimization. Probabilistic Graphical Models (2016)
R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun
Recurrent Neural Networks for Spatiotemporal Dynamics of Intrinsic Networks from fMRI Data. CoRR (2016)
R. Devon Hjelm, Sergey M. Plis, Vince D. Calhoun
Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data. CoRR (2016)
Antti Hyttinen, Sergey M. Plis, Matti Järvisalo, Frederick Eberhardt, David Danks
Causal Discovery from Subsampled Time Series Data by Constraint Optimization. CoRR (2016)
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
A Tool for Interactive Data Visualization: Application to Over 10, 000 Brain Imaging and Phantom MRI Data Sets. Frontiers Neuroinformatics 10 (2016)
Eduardo Castro, R. Devon Hjelm, Sergey M. Plis, Laurent Dinh, Jessica A. Turner, Vince D. Calhoun
Deep independence network analysis of structural brain imaging: A simulation study. MLSP (2015)
Sergey M. Plis, David Danks, Jianyu Yang
Mesochronal Structure Learning. UAI (2015)
Bradley T. Baker, Rogers F. Silva, Vince D. Calhoun, Anand D. Sarwate, Sergey M. Plis
Large scale collaboration with autonomy: Decentralized data ICA. MLSP (2015)
Eduardo Castro, Alvaro Ulloa, Sergey M. Plis, Jessica A. Turner, Vince D. Calhoun
Generation of synthetic structural magnetic resonance images for deep learning pre-training. ISBI (2015)
Sergey M. Plis, David Danks, Cynthia Freeman, Vince D. Calhoun
Rate-Agnostic (Causal) Structure Learning. NIPS (2015)

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Publication Activity (10 Years)

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Sergey M. Plis