Bayesian computational technique

On Cross Validation, Log Gaussian Cox Process and Variational Bayes

Hans Montcho, Ph.D. Student, Statistics

Apr 29, 10:00 - 12:00

B2 R5220; Zoom Meeting 99219689653

Bayesian computational technique Bayesian computational statistics latent Gaussian models Point patterns spital point patterns

This dissertation advances Bayesian computation by developing a cross validation approach to assess LGCPs defined on Euclidean, manifolds or network domains and improving skewed posterior approximations for LGMs.

Multilevel Bayesian Neural Networks

Nov 1, 12:00 - 13:00

B9 L2 R2322

Bayesian computational technique Applied Machine Learning

Abstract In this talk we consider the application of multilevel Monte Carlo for Bayesian computation tasks in machine learning. There has recently been a synergy of statisticsand machine learning, promoting the application and development of new methodologies.Based on this we promote the use of multilevel Monte Carlo, which is a technique used toreduce the cost to attain a particular order of MSE with trace-class neural network priors. We provide some theoretical insights, and demonstrate the performance of our methodologyon different model problems such as classification and reinforcement

Hans Montcho

Ph.D. Student, Statistics

Bayesian computational statistics machine learning Bayesian computational technique cross validation point processes statistics Python (Programming Language)

Hans Montcho is a Ph.D. Ph.D. candidate In Statistics at the King Abdullah University of Science and Technology (KAUST).