research
∙
10/01/2021
Confounder importance learning for treatment effect inference
We address applied and computational issues for the problem of multiple ...
share
research
∙
03/19/2021
Scalable computation for Bayesian hierarchical models
The article is about algorithms for learning Bayesian hierarchical model...
research
∙
06/05/2020
Exact inference for a class of non-linear hidden Markov models on general state spaces
Exact inference for hidden Markov models requires the evaluation of all ...
research
∙
06/05/2020
Exact inference for a class of non-linear hidden Markov models
Exact inference for hidden Markov models requires the evaluation of all ...
research
∙
03/28/2019
Bayesian prediction of jumps in large panels of time series data
We take a new look at the problem of disentangling the volatility and ju...
research
∙
03/26/2018
Scalable inference for crossed random effects models
We analyze the complexity of Gibbs samplers for inference in crossed ran...
research
∙
03/09/2018
Robust MCMC Sampling with Non-Gaussian and Hierarchical Priors in High Dimensions
A key problem in inference for high dimensional unknowns is the design o...
research
∙
10/30/2016