David T. Frazier

According to our database, David T. Frazier authored at least 13 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Simulation-based Bayesian inference under model misspecification.

Ryan P. Kelly, David J. Warne, David T. Frazier, David J. Nott, Michael U. Gutmann, Christopher C. Drovandi

CoRR, March, 2025

Loss-Based Variational Bayes Prediction.

David T. Frazier, Ruben Loaiza-Maya, Gael M. Martin, Bonsoo Koo

J. Comput. Graph. Stat., 2025

2024

Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference.

Ryan P. Kelly, David J. Nott, David T. Frazier, David J. Warne, Christopher C. Drovandi

Trans. Mach. Learn. Res., 2024

Testing Model Specification in Approximate Bayesian Computation Using Asymptotic Properties.

Andrés Ramírez-Hassan, David T. Frazier

J. Comput. Graph. Stat., 2024

Improving the Accuracy of Marginal Approximations in Likelihood-Free Inference via Localization.

Christopher C. Drovandi, David J. Nott, David T. Frazier

J. Comput. Graph. Stat., 2024

The Statistical Accuracy of Neural Posterior and Likelihood Estimation.

David T. Frazier, Ryan P. Kelly, Christopher C. Drovandi, David J. Warne

CoRR, 2024

2023

Modularized Bayesian analyses and cutting feedback in likelihood-free inference.

Atlanta Chakraborty, David J. Nott, Christopher C. Drovandi, David T. Frazier, Scott A. Sisson

Stat. Comput., February, 2023

Variational Bayes in State Space Models: Inferential and Predictive Accuracy.

David T. Frazier, Ruben Loaiza-Maya, Gael M. Martin

J. Comput. Graph. Stat., 2023

Misspecification-robust Sequential Neural Likelihood.

Ryan P. Kelly, David J. Nott, David T. Frazier, David J. Warne, Chris Drovandi

CoRR, 2023

2022

A comparison of likelihood-free methods with and without summary statistics.

Christopher C. Drovandi, David T. Frazier

Stat. Comput., 2022

Efficient Bayesian Synthetic Likelihood With Whitening Transformations.

Jacob W. Priddle, Scott A. Sisson, David T. Frazier, Ian W. Turner, Christopher C. Drovandi

J. Comput. Graph. Stat., 2022

2021

Robust Approximate Bayesian Inference With Synthetic Likelihood.

David T. Frazier, Christopher C. Drovandi

J. Comput. Graph. Stat., 2021

2020

Forecasting: theory and practice.

Fotios Petropoulos, Daniele Apiletti, Vassilios Assimakopoulos, Mohamed Zied Babai, Devon K. Barrow, Souhaib Ben Taieb, Christoph Bergmeir, Ricardo J. Bessa, Jakub Bijak, John E. Boylan, Jethro Browell, Claudio Carnevale, Jennifer L. Castle, Pasquale Cirillo, Michael P. Clements, Clara Cordeiro, Fernando Luiz Cyrino Oliveira, Shari De Baets, Alexander Dokumentov, Joanne Ellison, Piotr Fiszeder, Philip Hans Franses, David T. Frazier, Michael Gilliland, Mustafa Sinan Gönül, Paul Goodwin, Luigi Grossi, Yael Grushka-Cockayne, Mariangela Guidolin, Massimo Guidolin, Ulrich Gunter, Xiaojia Guo, Renato Guseo, Nigel Harvey, David F. Hendry, Ross Hollyman, Tim Januschowski, Jooyoung Jeon, Victor Richmond R. Jose, Yanfei Kang, Anne B. Koehler, Stephan Kolassa, Nikolaos Kourentzes, Sonia Leva, Feng Li

CoRR, 2020