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Julia Porcino

3 papers hereh-index 593 citations24 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2
  • last author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • stat.ME2
  • stat.AP1

identity via Semantic Scholar / OpenAlex

activity
20202024
most citedPerturbative adaptive importance sampling for Bayesian LOO cross-validation

1 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

stat.ME2024★ 1 cited

Perturbative adaptive importance sampling for Bayesian LOO cross-validation

Joshua C Chang, Xiangting Li, Tianyi Su +4

Importance sampling (IS) is an efficient stand-in for model refitting in performing (LOO) cross-validation (CV) on a Bayesian model. IS inverts the Bayesian update for a single obs…

stat.ME2022

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

Joshua C. Chang, Carson C. Chow, Julia Porcino

The Work Disability Functional Assessment Battery (WD-FAB) is a multidimensional item response theory (IRT) instrument designed for assessing work-related mental and physical funct…

stat.AP2020★ 1 cited

Regularized Bayesian calibration and scoring of the WD-FAB IRT model improves predictive performance over marginal maximum likelihood

Joshua C. Chang, Julia Porcino, Elizabeth K. Rasch +1

Item response theory (IRT) is the statistical paradigm underlying a dominant family of generative probabilistic models for test responses, used to quantify traits in individuals re…

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