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Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets.

, , , and . ICMLA, page 436-441. IEEE Computer Society, (2010)

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Parsing epileptic events using a Markov switching process model for correlated time series., , and . ICML (1), volume 28 of JMLR Workshop and Conference Proceedings, page 356-364. JMLR.org, (2013)A Hierarchical Dirichlet Process Model with Multiple Levels of Clustering for Human EEG Seizure Modeling., , and . ICML, icml.cc / Omnipress, (2012)Does the morphology of high-frequency (100-500 Hz) brain oscillations change during epileptic seizures?, , , and . ACSCC, page 461-465. IEEE, (2011)An unsupervised method for identifying regions that initiate seizures on intracranial EEG., and . EMBC, page 3091-3094. IEEE, (2011)Neural Design for Genetic Perturbation Experiments., , , and . CoRR, (2022)Semi-Supervised Anomaly Detection for EEG Waveforms Using Deep Belief Nets., , , and . ICMLA, page 436-441. IEEE Computer Society, (2010)Neural Design for Genetic Perturbation Experiments., , , and . ICLR, OpenReview.net, (2023)SystemMatch: optimizing preclinical drug models to human clinical outcomes via generative latent-space matching., , , , , , , , , and . CoRR, (2022)Modeling the complex dynamics and changing correlations of epileptic events., , and . Artif. Intell., (2014)