Web: http://arxiv.org/abs/2206.08420

June 20, 2022, 1:12 a.m. | Takuo Matsubara, Jeremias Knoblauch, François-Xavier Briol, Chris. J. Oates

stat.ML updates on arXiv.org arxiv.org

Discrete state spaces represent a major computational challenge to
statistical inference, since the computation of normalisation constants
requires summation over large or possibly infinite sets, which can be
impractical. This paper addresses this computational challenge through the
development of a novel generalised Bayesian inference procedure suitable for
discrete intractable likelihood. Inspired by recent methodological advances for
continuous data, the main idea is to update beliefs about model parameters
using a discrete Fisher divergence, in lieu of the problematic intractable
likelihood. …

arxiv bayesian bayesian inference inference

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