arXiv Open Access 2022

Nonlinear MCMC for Bayesian Machine Learning

James Vuckovic

Lihat Sumber

Abstrak

We explore the application of a nonlinear MCMC technique first introduced in [1] to problems in Bayesian machine learning. We provide a convergence guarantee in total variation that uses novel results for long-time convergence and large-particle ("propagation of chaos") convergence. We apply this nonlinear MCMC technique to sampling problems including a Bayesian neural network on CIFAR10.

Topik & Kata Kunci

stat.ML cs.LG math.PR

Penulis (1)

James Vuckovic

Format Sitasi

APA MLA BibTeX

Vuckovic, J. (2022). Nonlinear MCMC for Bayesian Machine Learning. https://arxiv.org/abs/2202.05621

Akses Cepat

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓