Bayesian neural networks and dimensionality reduction

no code implementations • 18 Aug 2020 • Deborshee Sen, Theodore Papamarkou, David Dunson

We attempt to solve these problems by deploying Markov chain Monte Carlo sampling algorithms (MCMC) for Bayesian inference in ANN models with latent variables.

Bayesian Inference Dimensionality Reduction +1

Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent states

no code implementations • 31 Oct 2018 • Rihui Ou, Deborshee Sen, Alexander L Young, David B Dunson

We propose a targeted sub-sampling (TASS) approach that over-samples observations corresponding to rare latent states when calculating the stochastic gradient of parameters associated with them.

Clustering Time Series +1