Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods · HackerPapers discussionshttps://hackerpaper.kaipfister.de/p/2107.08001/Collected HN comments and submissions linking this paper.enMon, 02 Nov 2026 11:16:22 GMTEfficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods — mentioned by saroshhttps://news.ycombinator.com/item?id=41869632urn:hackerpapers:mention:2107.08001:41869632Thu, 17 Oct 2024 13:46:52 GMT<p>Defer to other experts, but (briefly) normalizing flows are a method for constructing complex distributions by transforming a probability density through a series of invertible transformations. Normalizing flows are trained using a plain log-likelihood function, and they are capable of exact density evaluation and efficient sampling. See: Danilo Rezende and Shakir Mohamed. Variational inference with normalizing flows. In ICML, 2015. Link: https://bigdata.duke.edu/wp-content/uploads/2022/08/1505.057... Laurent Dinh, David Krueger, and Yoshua Bengio. Nice: Non-linear independent components…</p><p><a href="https://hackerpaper.kaipfister.de/p/2107.08001/">Paper and discussion history</a>. A mention is not an endorsement.</p>stat.ML