Search Results for author: Julia Porcino

Found 4 papers, 1 papers with code

Gradient-flow adaptive importance sampling for Bayesian leave one out cross-validation for sigmoidal classification models

no code implementations13 Feb 2024 Joshua C Chang, Xiangting Li, Shixin Xu, Hao-Ren Yao, Julia Porcino, Carson Chow

We introduce a set of gradient-flow-guided adaptive importance sampling (IS) transformations to stabilize Monte-Carlo approximations of point-wise leave one out cross-validated (LOO) predictions for Bayesian classification models.

Autoencoded sparse Bayesian in-IRT factorization, calibration, and amortized inference for the Work Disability Functional Assessment Battery

no code implementations20 Oct 2022 Joshua C. Chang, Carson C. Chow, Julia Porcino

We also analogize our multidimensional IRT model to probabilistic autoencoders, specifying an encoder function that amortizes the inference of ability parameters from item responses.

Bayesian Inference

Cannot find the paper you are looking for? You can Submit a new open access paper.