<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Bernhard Schölkopf | Global Pathogen Analysis Platform (GPAP) AI Research</title><link>https://gpap-project.github.io/author/bernhard-scholkopf/</link><atom:link href="https://gpap-project.github.io/author/bernhard-scholkopf/index.xml" rel="self" type="application/rss+xml"/><description>Bernhard Schölkopf</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 19 Feb 2025 00:00:00 +0000</lastBuildDate><image><url>https://gpap-project.github.io/media/logo.svg</url><title>Bernhard Schölkopf</title><link>https://gpap-project.github.io/author/bernhard-scholkopf/</link></image><item><title>Artificial intelligence for modelling infectious disease epidemics</title><link>https://gpap-project.github.io/publication/kraemer-2025-artificial/</link><pubDate>Wed, 19 Feb 2025 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/kraemer-2025-artificial/</guid><description/></item><item><title>Pyfectious: An individual-level simulator to discover optimal containment policies for epidemic diseases</title><link>https://gpap-project.github.io/publication/mehrjou-2023-pyfectious/</link><pubDate>Mon, 23 Jan 2023 00:00:00 +0000</pubDate><guid>https://gpap-project.github.io/publication/mehrjou-2023-pyfectious/</guid><description/></item></channel></rss>