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ORCIDYogatheesan Varatharajah
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2020 – today
- 2024
[j3]James L. Evans, Matthew T. Bramlet, Connor Davey, Eliot B. Bethke, Aaron T. Anderson, Graham Huesmann, Yogatheesan Varatharajah, Andrés Maldonado, Jennifer R. Amos, Bradley P. Sutton:
SEEG4D: a tool for 4D visualization of stereoelectroencephalography data. Frontiers Neuroinformatics 18 (2024)- 2023
- [c11]Teja Gupta, Neeraj Wagh, Samarth Rawal, Brent M. Berry, Gregory A. Worrell, Yogatheesan Varatharajah:
Tensor Decomposition of Large-scale Clinical EEGs Reveals Interpretable Patterns of Brain Physiology. NER 2023: 1-4 - 2022
- [j2]Krishnakant V. Saboo
, Chang Hu, Yogatheesan Varatharajah, Scott A. Przybelski, Robert I. Reid, Christopher G. Schwarz, Jonathan Graff-Radford, David S. Knopman, Mary M. Machulda, Michelle M. Mielke, Ronald C. Petersen, Paul M. Arnold, Gregory A. Worrell, David T. Jones, Clifford R. Jack Jr., Ravishankar K. Iyer, Prashanthi Vemuri:
Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging. NeuroImage 251: 119020 (2022) - [c10]Neeraj Wagh, Jionghao Wei, Samarth Rawal, Brent M. Berry, Yogatheesan Varatharajah:
Evaluating Latent Space Robustness and Uncertainty of EEG-ML Models under Realistic Distribution Shifts. NeurIPS 2022 - [i6]Neeraj Wagh, Jionghao Wei, Samarth Rawal, Brent M. Berry, Yogatheesan Varatharajah:
Assessing Robustness of EEG Representations under Data-shifts via Latent Space and Uncertainty Analysis. CoRR abs/2209.11233 (2022) - [i5]Teja Gupta, Neeraj Wagh, Samarth Rawal, Brent M. Berry, Gregory A. Worrell, Yogatheesan Varatharajah:
Tensor Decomposition of Large-scale Clinical EEGs Reveals Interpretable Patterns of Brain Physiology. CoRR abs/2211.13793 (2022) - 2021
- [c9]Neeraj Wagh, Jionghao Wei, Samarth Rawal, Brent M. Berry, Leland Barnard, Benjamin H. Brinkmann, Gregory A. Worrell, David T. Jones, Yogatheesan Varatharajah:
Domain-guided Self-supervision of EEG Data Improves Downstream Classification Performance and Generalizability. ML4H@NeurIPS 2021: 130-142 - [i4]Samarth Rawal, Yogatheesan Varatharajah:
SCORE-IT: A Machine Learning-based Tool for Automatic Standardization of EEG Reports. CoRR abs/2109.05694 (2021) - 2020
- [b1]Yogatheesan Varatharajah:
Learning more with less data using domain-guided machine learning: the case for health data analytics. University of Illinois Urbana-Champaign, USA, 2020 - [c8]Yogatheesan Varatharajah, Brent M. Berry, Boney Joseph, Irena Balzekas, Václav Kremen, Benjamin H. Brinkmann, Gregory A. Worrell, Ravishankar K. Iyer:
Electrophysiological Correlates of Brain Health Help Diagnose Epilepsy and Lateralize Seizure Focus. EMBC 2020: 3460-3464 - [c7]Krishnakant V. Saboo, Chang Hu, Yogatheesan Varatharajah, Prashanthi Vemuri, Ravishankar K. Iyer:
Predicting Longitudinal Cognitive Scores Using Baseline Imaging and Clinical Variables. ISBI 2020: 1326-1330 - [c6]Neeraj Wagh, Yogatheesan Varatharajah:
EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network. ML4H@NeurIPS 2020: 367-378 - [c5]Yogatheesan Varatharajah, Haotian Chen, Andrew Trotter, Ravishankar K. Iyer:
A Dynamic Human-in-the-loop Recommender System for Evidence-based Clinical Staging of COVID-19. HealthRecSys@RecSys 2020: 21-22 - [i3]Neeraj Wagh, Yogatheesan Varatharajah:
EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network. CoRR abs/2011.12107 (2020)
2010 – 2019
- 2019
- [c4]Yogatheesan Varatharajah, Krishnakant V. Saboo, Ravishankar K. Iyer, Scott A. Przybelski, Christopher G. Schwarz, Ronald C. Petersen, Clifford R. Jack, Prashanthi Vemuri:
A Joint Model for Predicting Structural and Functional Brain Health in Elderly Individuals. BIBM 2019: 1657-1664 - [c3]Krishnakant V. Saboo, Yogatheesan Varatharajah, Brent M. Berry, Michael R. Sperling, Richard J. T. Gorniak, Kathryn A. Davis, Barbara C. Jobst, Robert E. Gross, Bradley Lega, Sameer A. Sheth, Michael J. Kahana, Michal T. Kucewicz, Gregory A. Worrell, Ravishankar K. Iyer:
A Computationally Efficient Model for Predicting Successful Memory Encoding Using Machine-Learning-based EEG Channel Selection. NER 2019: 323-327 - 2018
- [i2]Yogatheesan Varatharajah, Brent M. Berry, Sanmi Koyejo, Ravishankar K. Iyer:
A Contextual-bandit-based Approach for Informed Decision-making in Clinical Trials. CoRR abs/1809.00258 (2018) - [i1]Yogatheesan Varatharajah, Brent M. Berry, Jan Cimbalnik, Václav Kremen, Jamie Van Gompel, Matt Stead, Benjamin H. Brinkmann, Ravishankar K. Iyer, Gregory A. Worrell:
Integrating Artificial Intelligence with Real-time Intracranial EEG Monitoring to Automate Interictal Identification of Seizure Onset Zones in Focal Epilepsy. CoRR abs/1812.06234 (2018) - 2017
- [j1]Yogatheesan Varatharajah, Ravishankar K. Iyer, Brent M. Berry, Gregory A. Worrell, Benjamin H. Brinkmann:
Seizure Forecasting and the Preictal State in Canine Epilepsy. Int. J. Neural Syst. 27(1): 1650046:1-1650046:12 (2017) - [c2]Yogatheesan Varatharajah, Brent M. Berry, Zbigniew T. Kalbarczyk, Benjamin H. Brinkmann, Gregory A. Worrell, Ravishankar K. Iyer:
Inter-ictal Seizure Onset Zone localization using unsupervised clustering and Bayesian Filtering. NER 2017: 533-539 - [c1]Yogatheesan Varatharajah, Min Jin Chong, Krishnakant V. Saboo, Brent M. Berry, Benjamin H. Brinkmann, Gregory A. Worrell, Ravishankar K. Iyer:
EEG-GRAPH: A Factor-Graph-Based Model for Capturing Spatial, Temporal, and Observational Relationships in Electroencephalograms. NIPS 2017: 5371-5380
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last updated on 2024-09-13 01:39 CEST by the dblp team
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