Accelerating Bayesian Synthetic Likelihood With the Graphical Lasso

by David Nott
Published 2019

Marginally Calibrated Deep Distributional Regression

by Nadja Klein, DAVID NOTT, Michael Smith
Published 2021

Gaussian Variational Approximation With a Factor Covariance Structure

by Victor Ong, David Nott, Michael Smith
Published 2018

High-dimensional Copula Variational Approximation through Transformation

by Michael Smith, Ruben Loaiza-Maya, David Nott
Published 2021

Variational Bayes With Intractable Likelihood

by Minh-Ngoc Tran, David Nott, Robert Kohn
Published 2018

Bayesian Synthetic Likelihood

by Leah Price, Christopher Drovandi, Anthony Lee, David Nott
Published 2018

Bayesian Deep Net GLM and GLMM

by Minh-Ngoc Tran, Nghia Nguyen, David Nott, Robert Kohn
Published 2020

Assessment and adjustment of approximate inference algorithms using the law of total variance

by Xuejun Yu, David Nott, Minh-Ngoc Tran, Nadja Klein
Published 2022

Using History Matching for Prior Choice

by Wang Xueou, David Nott, Christopher Drovandi, Kerrie Mengersen, Michael Evans
Published 2018

Multilevel Monte Carlo in Approximate Bayesian Computation

by Ajay Jasra, Seongil Jo, David Nott, Christine Shoemaker, Raul Tempone
Published 2019