no code implementations • 19 Apr 2023 • Hongjing Xia, Joshua C. Chang, Sarah Nowak, Sonya Mahajan, Rohit Mahajan, Ted L. Chang, Carson C. Chow
We used survival analysis to quantify the impact of postdischarge evaluation and management (E/M) services in preventing hospital readmission or death.
no code implementations • 20 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.
no code implementations • 28 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.
1 code implementation • ICLR 2021 • Joshua C. Chang, Patrick Fletcher, Jungmin Han, Ted L. Chang, Shashaank Vattikuti, Bart Desmet, Ayah Zirikly, Carson C. Chow
However, sparsity in representation decoding does not necessarily imply sparsity in the encoding of representations from the original data features.
1 code implementation • 5 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.
no code implementations • 21 Feb 2017 • Joshua C. Chang
Consider the problem of modeling hysteresis for finite-state random walks using higher-order Markov chains.
2 code implementations • 10 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