3 papers
cs.LG2026
Bayesian Inference of Psychometric Variables From Brain and Behavior in Implicit Association Tests
Christian A. Kothe, Sean Mullen, Michael V. Bronstein +7
Objective. We establish a principled method for inferring mental health related psychometric variables from neural and behavioral data using the Implicit Association Test (IAT) as…
cs.LG2024
Latent Variable Double Gaussian Process Model for Decoding Complex Neural Data
Navid Ziaei, Joshua J. Stim, Melanie D. Goodman-Keiser +4
Non-parametric models, such as Gaussian Processes (GP), show promising results in the analysis of complex data. Their applications in neuroscience data have recently gained tractio…
cs.LG2024
A Bayesian Gaussian Process-Based Latent Discriminative Generative Decoder (LDGD) Model for High-Dimensional Data
Navid Ziaei, Behzad Nazari, Uri T. Eden +2
Extracting meaningful information from high-dimensional data poses a formidable modeling challenge, particularly when the data is obscured by noise or represented through different…