Search Results for author: Joshua C. Chang

Found 7 papers, 3 papers with code

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

Interpretable (not just posthoc-explainable) medical claims modeling for discharge placement to prevent avoidable all-cause readmissions or death

no code implementations28 Aug 2022 Joshua C. Chang, Ted L. Chang, Carson C. Chow, Rohit Mahajan, Sonya Mahajan, Joe Maisog, Shashaank Vattikuti, Hongjing Xia

We developed an inherently interpretable multilevel Bayesian framework for representing variation in regression coefficients that mimics the piecewise linearity of ReLU-activated deep neural networks.

Feature Engineering regression

Probabilistically-autoencoded horseshoe-disentangled multidomain item-response theory models

1 code implementation5 Dec 2019 Joshua C. Chang, Shashaank Vattikuti, Carson C. Chow

By binding the generative IRT model to a Bayesian neural network (forming a probabilistic autoencoder), one obtains a scoring algorithm consistent with the interpretable Bayesian model.

Determination of hysteresis in finite-state random walks using Bayesian cross validation

no code implementations21 Feb 2017 Joshua C. Chang

Consider the problem of modeling hysteresis for finite-state random walks using higher-order Markov chains.

Asymptotic convergence in distribution of the area bounded by prevalence-weighted Kaplan-Meier curves using empirical process modeling

2 code implementations10 Jan 2017 Aaron Heuser, Minh Huynh, Joshua C. Chang

The Kaplan-Meier product-limit estimator is a simple and powerful tool in time to event analysis.

Methodology Probability Statistics Theory Statistics Theory

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