Drausin F. Wulsin

Affiliations: 
2013 Bioengineering University of Pennsylvania, Philadelphia, PA, United States 
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Brian Litt grad student 2013 Penn
 (Bayesian Nonparametric Modeling of Epileptic Events.)
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Publications

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Davis KA, Ung H, Wulsin D, et al. (2015) Mining continuous intracranial EEG in focal canine epilepsy: Relating interictal bursts to seizure onsets. Epilepsia
Wulsin DF, Fox EB, Litt B. (2014) Modeling the Complex Dynamics and Changing Correlations of Epileptic Events. Artificial Intelligence. 216: 55-75
Pearce A, Wulsin D, Blanco JA, et al. (2013) Temporal changes of neocortical high-frequency oscillations in epilepsy. Journal of Neurophysiology. 110: 1167-79
Wulsin DF, Fox EB, Litt B. (2013) Parsing epileptic events using a Markov switching process for correlated time series 30th International Conference On Machine Learning, Icml 2013. 356-364
Wulsin D, Jensen S, Litt B. (2012) A hierarchical dirichlet process model with multiple levels of clustering for human EEG seizure modeling Proceedings of the 29th International Conference On Machine Learning, Icml 2012. 1: 57-64
Wulsin D, Litt B. (2011) An unsupervised method for identifying regions that initiate seizures on intracranial EEG. Conference Proceedings : ... Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual Conference. 2011: 3091-4
Viventi J, Kim DH, Vigeland L, et al. (2011) Flexible, foldable, actively multiplexed, high-density electrode array for mapping brain activity in vivo. Nature Neuroscience. 14: 1599-605
Wulsin DF, Gupta JR, Mani R, et al. (2011) Modeling electroencephalography waveforms with semi-supervised deep belief nets: fast classification and anomaly measurement. Journal of Neural Engineering. 8: 036015
Pearce A, Wulsin D, Litt B, et al. (2011) Does the morphology of high-frequency (100-500 Hz) brain oscillations change during epileptic seizures? Conference Record - Asilomar Conference On Signals, Systems and Computers. 461-465
Wulsin D, Blanco J, Mani R, et al. (2010) Semi-supervised anomaly detection for EEG waveforms using deep belief nets Proceedings - 9th International Conference On Machine Learning and Applications, Icmla 2010. 436-441
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