jona-sassenhagen/SASICA
SemiAutomatic Selection of Independent Components for Artifact correction in the EEG
HDDM is a python module that implements Hierarchical Bayesian parameter estimation of Drift Diffusion Models (via PyMC).
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SemiAutomatic Selection of Independent Components for Artifact correction in the EEG
Sent2Vec encoder and training code from the paper "Skip-Thought Vectors"
Highly extensible deep learning framework
Public repository.