variational inference
books
papers
software
Links to this note
- approximate bayesian computation
- free energy principle
- single-cell transcriptome analysis
- probabilistic inference
- Bayesian brain hypothesis
- turing.jl
- scVI
- pyro
- Variational inference a review for statisticians by David Blei et al in 2017
- Variational inference by Chieh Wu in 2015
- The Helmholtz Machine by Peter Dayan, Geoffrey Hinton, Radford Neal, and Richard Zemel in 1995
- Mean field variational inference
- Information, physics, and computation by Marc Mezard and Andrea Montanari in 2009
- Du Phan
- Du Phan's implementation of Statistical rethinking in pyro
- Build, Compute, Critique, Repeat Data Analysis with latent variable models by David Blei in 2014
- Bayesian Inference for a Generative Model of Transcriptome Profiles from Single-cell RNA Sequencing by Romain Lopez, Michael Jordan, Nir Yosef et al in 2018
- Automatic Differentiation Variational Inference by Dustin Tran, Andrew Gelman, David Blei et al in 2016
- A free energy principle for a particular physics by Karl Friston in 2019
- A high-bias, low-variance introduction to Machine Learning for physicists by Pankaj Mehta, Charles Fisher, David Schwab, et al in 2018