Variational Inference for Cutting Feedback in Misspecified Models

Michael Smith, Melbourne Business School

03.11.2023

1:15 pm - 2:45 pm

LMU Munich, Department of Statistics and via zoom

This talk delves into Bayesian analyses, focusing on the challenging task of cutting feedback in joint Bayesian models when certain terms are misspecified. It introduces cut posterior distributions as solutions to constrained optimization problems, offering a novel perspective.

#lecture

Subscribe to RSS Events feed

Colloquium • 06.05.2026 • LMU Munich, Department of Statistics and via zoom

Data Thinning and Beyond

06.05.26, 4:15-5:45 pm: Daniela Witten from the University of Washington

Lecture • 12.06.2026 • LMU Munich, CAS, Seestr. 13, Munich

Analyzing Feature Interactions Through Local Effects in Machine Learning Models

As part of the CAS Research Focus, Giuseppe Casalicchio talks about interpretable machine learning that develops methods.

Variational Inference for Cutting Feedback in Misspecified Models

Michael Smith, Melbourne Business School

Related