A scalable Bayesian SVC framework that performs predictor-level selection of entire coefficient surfaces through a spike-and-slab group lasso (SSGL) prior on basis expansion coefficients
Derive general density for scale mixtures of complex Gaussians and use them as shrinkage priors in Bayesian complex linear regression
A Comparative Study of Bayesian Neural Networks and Machine Learning Based on COVID-19 Image Classification
Bayesian hierarchical modeling for latency estimation of event-related potentials
We propose a semiparametric latent ANOVA model (SLAM) that unifies inference on ERP components and their association to covariates. SLAM modelsERP waveforms via a structured Gaussian process prior that encodes ERP latency in its derivative and links the subject-level latencies to covariates using a latent ANOVA.
Bayesian hierarchical modeling for latency and amplitude estimation of event-related potentials
Bayesian hierarchical modeling for latency estimation of event-related potentials
Bayesian spatiotemporal modeling of CV-fMRI via kernel convolutions