talks
Selected talk slides.
| Date | Talk | |
|---|---|---|
| Dec 2024 | Deep Kernel Posterior Learning under Infinite Variance Prior Weights | slides |
| Jun 2024 | Likelihood Based Inference in Fully and Partially Observed Exponential Family Graphical Models with Intractable Normalizing Constants | slides |
| Jun 2023 | Bayesian Covariate-Dependent Quantile Directed Acyclic Graphical Models for Individualized Inference | slides |
| Jun 2022 | Graphical Evidence | slides · video |
| Mar 2022 | Bayesian Robust Learning in Chain Graph Models for Integrative Pharmacogenomics | slides |
| Dec 2020 | Beyond Matérn: on the class of confluent hypergeometric covariance functions for Gaussian process modeling | slides |
| Aug 2019 | Horseshoe regularization for machine learning in complex and deep models | slides |
| May 2018 | The graphical horseshoe estimator for inverse covariance matrices | slides |
| Nov 2016 | Default Bayes and prediction problems with global-local shrinkage priors | slides |
| Jan 2015 | The horseshoe+ estimator of sparse signals | slides |
| Jul 2014 | Bayesian feature selection in high-dimensional regression in presence of correlated noise | slides |
| Oct 2012 | Joint high-dimensional Bayesian variable and covariance selection with an application to eQTL analysis | slides |
| Feb 2012 | Simulation-based maximum likelihood inference for partially observed Markov process models | slides |