From 8ce95984b9179d4774651b734271435ce369f2a3 Mon Sep 17 00:00:00 2001 From: "William J. Wilkinson" Date: Thu, 11 May 2023 15:25:45 +0100 Subject: [PATCH] Update README.md --- README.md | 16 ++++++++++------ 1 file changed, 10 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index 0c0739b..10a1299 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ Bayes-Newton is a library for approximate inference in Gaussian processes (GPs) Bayes-Newton provides a unifying view of approximate Bayesian inference, and allows for the combination of many models (e.g. GPs, sparse GPs, Markov GPs, sparse Markov GPs) with the inference method of your choice (VI, EP, Laplace, Linearisation). For a full list of the methods implemented scroll down to the bottom of this page. The methodology is outlined in the following article: -* W.J. Wilkinson, S. Särkkä, and A. Solin (2021): **Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees**. [*arXiv preprint arXiv:2111.01721*](https://arxiv.org/abs/2111.01721). +* W.J. Wilkinson, S. Särkkä, and A. Solin: [**Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees**. *JMLR volume 24 (2023)*](https://www.jmlr.org/papers/volume24/21-1298/21-1298.pdf). ## Installation @@ -80,12 +80,16 @@ Full demos are available [here](https://github.com/AaltoML/BayesNewton/tree/main ## Citing Bayes-Newton ``` -@article{wilkinson2021bayesnewton, - title = {{B}ayes-{N}ewton Methods for Approximate {B}ayesian Inference with {PSD} Guarantees}, - author = {Wilkinson, William J. and S\"arkk\"a, Simo and Solin, Arno}, - journal={arXiv preprint arXiv:2111.01721}, - year={2021} +@article{wilkinson2023bayes, + title={{B}ayes--{N}ewton Methods for Approximate {B}ayesian Inference with {PSD} Guarantees}, + author={Wilkinson, William J and S{\"a}rkk{\"a}, Simo and Solin, Arno}, + journal={Journal of Machine Learning Research}, + volume={24}, + number={83}, + pages={1--50}, + year={2023} } + ``` ## Implemented Models