<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Mikko S. Pakkanen | Global Pathogen Analysis Platform (GPAP) AI Research</title><link>https://gpap-project.github.io/author/mikko-s.-pakkanen/</link><atom:link href="https://gpap-project.github.io/author/mikko-s.-pakkanen/index.xml" rel="self" type="application/rss+xml"/><description>Mikko S. Pakkanen</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Tue, 01 Aug 2023 00:00:00 +0000</lastBuildDate><image><url>https://gpap-project.github.io/media/logo.svg</url><title>Mikko S. Pakkanen</title><link>https://gpap-project.github.io/author/mikko-s.-pakkanen/</link></image><item><title>Unifying incidence and prevalence under a time-varying general branching process</title><link>https://gpap-project.github.io/publication/pakkanen-2021-unifying/</link><pubDate>Tue, 01 Aug 2023 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/pakkanen-2021-unifying/</guid><description/></item><item><title>Intrinsic Randomness in Epidemic Modelling Beyond Statistical Uncertainty</title><link>https://gpap-project.github.io/publication/penn-2022-intrinsic/</link><pubDate>Thu, 01 Jun 2023 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/penn-2022-intrinsic/</guid><description/></item><item><title>$$\pi $$VAE: a stochastic process prior for Bayesian deep learning with MCMC</title><link>https://gpap-project.github.io/publication/mishra-2022-stochastic/</link><pubDate>Mon, 17 Oct 2022 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/mishra-2022-stochastic/</guid><description/></item></channel></rss>