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To do ===== [ ] BCI utility & another metric i don't recall [ ] DIC or BF / TEST [ ] Posterior predictive check, bayesian p-value - check literature for important statistics - P300 feature extractions https://projecteuclid.org/journals/annals-of-statistics/volume-22/issue-3/Posterior-Predictive-p-Values/10.1214/aos/1176325622.full https://pubmed.ncbi.nlm.nih.gov/19174332/ www.stat.columbia.edu/~gelman/research/published/A6n41.pdf [ ] pre-estimate smoothness to choose a parameter [ ] EEGNet https://github.com/vlawhern/arl-eegmodels/blob/master/examples/ERP.py Notes for next meeting ====================== Ran the experiment by reversing the order of the initialization - Basically what I expected: the initialization dictates the result, and the prior has almost no effect (some small shrinkage). The posterior for the shrinkage factor is not longer decreasing. Turns out a1 should be chosen to be 1 instead Backlog ======= Commands ======== ssh simon@192.168.0.208 scp <files> simon@simfont:/home/simon/Documents/BCI/experiments/test3/chains # get from GL scp simfont@greatlakes-xfer.arc-ts.umich.edu:./Documents/BCI/experiments/k114/chains/* ./experiments/k114/chains
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Bayesian Functional Factor Model for EEG-Based Brain-Computer Interfaces
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