Joint mixed membership modeling of multivariate longitudinal and survival data for learning the individualized disease progression

Y He, X Song, K Kang - The Annals of Applied Statistics, 2024‏ - projecteuclid.org
Joint mixed membership modeling of multivariate longitudinal and survival data for learning
the individualized disease progressi Page 1 The Annals of Applied Statistics 2024, Vol. 18 …

Deep Discrete Encoders: Identifiable Deep Generative Models for Rich Data with Discrete Latent Layers

S Lee, Y Gu - arxiv preprint arxiv:2501.01414, 2025‏ - arxiv.org
In the era of generative AI, deep generative models (DGMs) with latent representations have
gained tremendous popularity. Despite their impressive empirical performance, the …

Inferring latent structure in ecological communities via barcodes

B Scherting, DB Dunson - arxiv preprint arxiv:2412.08793, 2024‏ - arxiv.org
Accelerating global biodiversity loss has highlighted the role of complex relationships and
shared patterns among species in mediating responses to environmental changes. The …

[PDF][PDF] Exploratory General-response Cognitive Diagnostic Models with Higher-order Structures

J Liu, S Lee, Y Gu‏ - sites.stat.columbia.edu
Abstract Cognitive Diagnostic Models (CDMs) are popular discrete latent variable models in
educational and psychological measurement. While existing CDMs mainly focus on binary …

[PDF][PDF] Bayesian Q Matrix Estimation of Saturated Diagnostic Classification Models Using NIMBLE

CW Liu‏ - osf.io
Diagnostic classification models (DCMs) constitute a subset of restricted latent class models
in which latent classes are constrained by an expert-specified Q matrix reflecting students' …

[PDF][PDF] Inferring Individual Attributes Using Testlet-Based Visual Analogue Scaling and Beta Copula Diagnostic Classification Models

CW Liu‏ - osf.io
This paper explores the inference of the latent attributes of respondents using testlet-based
visual analogue scaling (VAS), which comprises multiple items ranging from 0% to 100 …