Xi'an's Og

A new season of the One World Approximate Bayesian Inference (OWABI) Seminar is about to start!

The 1^st OWABI talk of the Season will be given by François-Xavier Briol (University College London). who will talk about “Multilevel neural simulation-based inference” on Thursday the 30th October at 11am UK time.

Abstract

Neural simulation-based inference (SBI) is a popular set of methods for Bayesian inference when models are only available in the form of a simulator. These methods are widely used in the sciences and engineering, where writing down a likelihood can be significantly more challenging than constructing a simulator. However, the performance of neural SBI can suffer when simulators are computationally expensive, thereby limiting the number of simulations that can be performed. In this paper, we propose a novel approach to neural SBI which leverages multilevel Monte Carlo techniques for settings where several simulators of varying cost and fidelity are available. We demonstrate through both theoretical analysis and extensive experiments that our method can significantly enhance the accuracy of SBI methods given a fixed computational budget.

Keywords: Multifidelity, neural SBI, multi-level Monte Carlomultilevel Monte Carlo

This entry was posted on October 17, 2025 at 12:27 am and is filed under Statistics with tags ABC, approximate Bayesian inference, Bayesian inference, Bayesian neural networks, multi-level Monte Carlo, multifidelity, multilevel Monte Carlo, neural SBI, OWABI, simulation-based inference, UCL, University College London, University of Warwick, webinar. You can follow any responses to this entry through the RSS 2.0 feed. You can leave a response, or trackback from your own site.