IEEE

Dirichlet Process Mixture of Mixtures Model for Unsupervised Subword Modeling

Abstract: We develop a parallelizable Markov chain Monte Carlo sampler for a Dirichlet process mixture of mixtures model. Our sampler jointly infers a codebook and clusters. The codebook is a global ...
JSTOR Daily

Bayesian Semiparametric Estimation of Discrete Duration Models: An Application of the Dirichlet Process Prior

This paper proposes a Bayesian estimator for a discrete time duration model which incorporates a non-parametric specification of the unobserved heterogeneity distribution, through the use of a ...
JSTOR Daily

Clustering Distributions with the Marginalized Nested Dirichlet Process

We introduce a marginal version of the nested Dirichlet process to cluster distributions or histograms. We apply the model to cluster genes by patterns of gene-gene interaction. The proposed approach ...
Self

Here’s What ‘Processing’ Trauma Really Means—and How It Helps You Heal

The concept of “processing” trauma has become ubiquitous; #TraumaProcessing has more than a million views on TikTok, there’s no shortage of trauma-focused therapists sharing coping strategies on ...
GitHub

Rational Model of Categorization

This rational model of categorization is proposed by Anderson (1991) and extended by Sanborn, Griffiths, and Navarro (2010). This model is identical to Dirichlet process mixture model with either ...