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<rss version="2.0"><channel><description>postdoc @ uni oxford. machine learning. climate. statistics.&#xA;&#xA;web: treigerm.github.io</description><link>https://bsky.app/profile/treichelt.bsky.social</link><title>@treichelt.bsky.social - Tim Reichelt</title><item><link>https://bsky.app/profile/treichelt.bsky.social/post/3mbqs5uhuas2d</link><description>Ever wondered whether there&#39;s a principled way to calibrate all those parameters controlling climate models? In our new paper we show how to calibrate climate model parameterizations using ideas from Bayesian experimental design: https://doi.org/10.1088/3049-4753/ae2edb . (1/N)</description><pubDate>06 Jan 2026 10:56 +0000</pubDate><guid isPermaLink="false">at://did:plc:3mlzcgcd7mat2lb4u5txvb3b/app.bsky.feed.post/3mbqs5uhuas2d</guid></item><item><link>https://bsky.app/profile/treichelt.bsky.social/post/3lnkqetcyvs2f</link><description>I&#39;ll be at @egu.eu 2025 next week in Vienna. You can catch me on Monday at 14:05 in Room 2.92 talking about &#34;ClimateBenchPress: A Benchmark for Compression of Climate Data&#34;. I&#39;ll be at EGU the whole week so let me know if you want to chat about (neural) compression for climate or anything else!&#xA;&#xA;[contains quote post or other embedded content]</description><pubDate>24 Apr 2025 12:44 +0000</pubDate><guid isPermaLink="false">at://did:plc:3mlzcgcd7mat2lb4u5txvb3b/app.bsky.feed.post/3lnkqetcyvs2f</guid></item></channel></rss>