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Probabilistic modeling of time series based on Deep Neural Hidden Semi-Markov Models. Biosignals-specific (EEG) implementation.

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Deep Neural Dynamic Bayesian Networks

Python code of the paper Deep Neural Dynamic Bayesian Networks applied to EEG sleep spindles modeling by Carlos Loza and Laura Colgin.

Main class mimics a tensorflow probability distribution with sampling and scoring (i.e. log-probabilities) functionalities.

Requirements

  • Python 3.8 or later
  • tensorflow
  • tensorflow probability
  • sklearn
  • numpy
  • pandas
  • scipy

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Probabilistic modeling of time series based on Deep Neural Hidden Semi-Markov Models. Biosignals-specific (EEG) implementation.

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eeg graphical-models bayesian-networks deep-probabilistic-models

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