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#bayesian

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MediaFaro News Digest<p>Sunken British superyacht Bayesian is raised from the seabed.</p><p>A superyacht that sank off the coast of the Italian island of Sicily last year has been raised from the seabed by a specialist salvage team.</p><p>Seven of the 22 people on board died in the sinking, including the vessel's owner, British tech tycoon Mike Lynch and his 18-year-old daughter.</p><p>The cause of the sinking is still under investigation.</p><p><a href="https://mediafaro.org/article/20250620-sunken-british-superyacht-bayesian-is-raised-from-the-seabed?mf_channel=mastodon&amp;action=forward" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">mediafaro.org/article/20250620</span><span class="invisible">-sunken-british-superyacht-bayesian-is-raised-from-the-seabed?mf_channel=mastodon&amp;action=forward</span></a></p><p><a href="https://mastodon.mediafaro.org/tags/Italy" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Italy</span></a> <a href="https://mastodon.mediafaro.org/tags/UK" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>UK</span></a> <a href="https://mastodon.mediafaro.org/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://mastodon.mediafaro.org/tags/MikeLynch" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MikeLynch</span></a></p>
tagesschau<p>Vor Sizilien: Luxusjacht "Bayesian" wird geborgen</p><p>Die Bergung des 56 Meter langen Segelschiffes hatte sich mehrfach verzögert. Nun ist es an der Oberfläche. Bei ihrem Untergang starben der britische Milliardär Mike Lynch und sechs weitere Insassen.</p><p>➡️ <a href="https://www.tagesschau.de/ausland/europa/bayesian-bergung-102.html?at_medium=mastodon&amp;at_campaign=tagesschau.de" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">tagesschau.de/ausland/europa/b</span><span class="invisible">ayesian-bergung-102.html?at_medium=mastodon&amp;at_campaign=tagesschau.de</span></a></p><p><a href="https://ard.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://ard.social/tags/Schiffsungl%C3%BCck" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Schiffsunglück</span></a></p>
PLOS Biology<p>Rewarding animals to accurately report their subjective <a href="https://fediscience.org/tags/percept" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>percept</span></a> is challenging. This study formalizes this problem and overcomes it with a <a href="https://fediscience.org/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> method for estimating an animal’s subjective percept in real time during the experiment <span class="h-card" translate="no"><a href="https://fediscience.org/@PLOSBiology" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>PLOSBiology</span></a></span> <a href="https://plos.io/3HaxiuB" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">plos.io/3HaxiuB</span><span class="invisible"></span></a></p>
Daniel Lakeland<p><a href="https://aeon.co/essays/no-schrodingers-cat-is-not-alive-and-dead-at-the-same-time" rel="nofollow noopener noreferrer" target="_blank"><span class="invisible">https://</span><span class="ellipsis">aeon.co/essays/no-schrodingers</span><span class="invisible">-cat-is-not-alive-and-dead-at-the-same-time</span></a></p><p>This is a pretty good article for showing how confused the interpretation of QM is. And its a good article to understand why i personally side with Bohm and Bell in thinking the pilot wave theory is the one most reasonable to believe. Because the pilot wave theory has the following quality. The theory is a mapping from initial position at time t=0 to final position at time t=1...Its deterministic, but our knowledge of the initial condition is not<br><a href="https://mastodon.sdf.org/tags/quantum" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>quantum</span></a> <a href="https://mastodon.sdf.org/tags/bohm" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bohm</span></a> <a href="https://mastodon.sdf.org/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a></p>
Peter Henry<p>What the report on the sinking of the <a href="https://mastodonapp.uk/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> boils down to was that the yacht was unseaworthy when it was built. Stupidly tall mast was just a vanity project - tragedy</p>
tagesschau<p>Vorläufiger Bericht: Luxusjacht "Bayesian" sank wegen extremen Winds</p><p>Bei dem Untergang der "Bayesian" vor Sizilien kamen im vergangenen Jahr sieben Menschen ums Leben. Nun gibt ein vorläufiger Bericht Hinweise auf die Unglücksursache der Luxusjacht, die eigentlich als "unsinkbar" galt.</p><p>➡️ <a href="https://www.tagesschau.de/ausland/europa/bayesian-bericht-unglueck-100.html?at_medium=mastodon&amp;at_campaign=tagesschau.de" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">tagesschau.de/ausland/europa/b</span><span class="invisible">ayesian-bericht-unglueck-100.html?at_medium=mastodon&amp;at_campaign=tagesschau.de</span></a></p><p><a href="https://ard.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://ard.social/tags/Schiffsungl%C3%BCck" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Schiffsunglück</span></a></p>
safest_integer<p>The new <a href="https://mastodon.social/tags/pope" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>pope</span></a> has a degree in <a href="https://mastodon.social/tags/mathematics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mathematics</span></a> and wrote a <a href="https://mastodon.social/tags/PhD" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PhD</span></a> thesis on "The role of the local prior" which I assume is a contribution to <a href="https://mastodon.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://mastodon.social/tags/statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statistics</span></a>. </p><p><a href="https://en.m.wikipedia.org/wiki/Pope_Leo_XIV" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">en.m.wikipedia.org/wiki/Pope_L</span><span class="invisible">eo_XIV</span></a></p>
Mathematik aus Karlsruhe<p>Modell253: Nadja and Moussa focus on the intersection of statistics and machine learning, in paticular on Bayesian methods, which allow to incorporate prior knowledge, quantify incertainties, and bring insides into the „black boxes“ of machine learning.</p><p><a href="https://modellansatz.de/bayesian-learning" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">modellansatz.de/bayesian-learn</span><span class="invisible">ing</span></a></p><p><a href="https://podcasts.social/tags/Mathematics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Mathematics</span></a> <a href="https://podcasts.social/tags/DataScience" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>DataScience</span></a> <a href="https://podcasts.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://podcasts.social/tags/Podcast" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Podcast</span></a></p>
Martin Modrák<p>I am trying to get a better sense of the literature on frequentist properties of Bayesian posterior distributions - both empirical and theoretical. Do you have any recommendations on stuff I should not miss? <a href="https://bayes.club/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>stats</span></a> <a href="https://bayes.club/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a> <a href="https://bayes.club/tags/LitReviews" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>LitReviews</span></a></p>
tagesschau<p>Die schwierige Bergung der Luxusjacht "Bayesian"</p><p>Eine riesige Luxusjacht sinkt im Mittelmeer: Das Unglück der "Bayesian", bei dem sieben Menschen starben, sorgte 2024 für Schlagzeilen und Spekulationen. Nun soll das Wrack geborgen werden, doch die Aktion verzögert sich.</p><p>➡️ <a href="https://www.tagesschau.de/ausland/europa/bayesian-bergung-100.html?at_medium=mastodon&amp;at_campaign=tagesschau.de" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">tagesschau.de/ausland/europa/b</span><span class="invisible">ayesian-bergung-100.html?at_medium=mastodon&amp;at_campaign=tagesschau.de</span></a></p><p><a href="https://ard.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a></p>
💧🌏 Greg Cocks<p>Environmental &amp; Anthropogenic Influences On Fire Patterns In Tropical Dry Deciduous Forests<br>--<br><a href="https://doi.org/10.1038/s41598-025-98051-7" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1038/s41598-025-980</span><span class="invisible">51-7</span></a> &lt;-- shared paper<br>--<br><a href="https://techhub.social/tags/GIS" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GIS</span></a> <a href="https://techhub.social/tags/spatial" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatial</span></a> <a href="https://techhub.social/tags/mapping" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mapping</span></a> <a href="https://techhub.social/tags/wildfire" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>wildfire</span></a> <a href="https://techhub.social/tags/fire" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>fire</span></a> <a href="https://techhub.social/tags/busgfire" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>busgfire</span></a> <a href="https://techhub.social/tags/nvironmental" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>nvironmental</span></a> <a href="https://techhub.social/tags/anthropogenic" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>anthropogenic</span></a> <a href="https://techhub.social/tags/influences" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>influences</span></a> <a href="https://techhub.social/tags/humanimpacts" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>humanimpacts</span></a> <a href="https://techhub.social/tags/deciduous" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>deciduous</span></a> <a href="https://techhub.social/tags/forests" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>forests</span></a> <a href="https://techhub.social/tags/firepatterns" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>firepatterns</span></a> <a href="https://techhub.social/tags/spatialanalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatialanalysis</span></a> <a href="https://techhub.social/tags/tropical" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tropical</span></a> <a href="https://techhub.social/tags/ecosystems" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ecosystems</span></a> <a href="https://techhub.social/tags/management" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>management</span></a> <a href="https://techhub.social/tags/tree" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tree</span></a> <a href="https://techhub.social/tags/vegetation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>vegetation</span></a> <a href="https://techhub.social/tags/spatiotemporal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatiotemporal</span></a> <a href="https://techhub.social/tags/hotspots" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hotspots</span></a> <a href="https://techhub.social/tags/india" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>india</span></a> <a href="https://techhub.social/tags/Satpura" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Satpura</span></a> <a href="https://techhub.social/tags/tiger" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tiger</span></a> <a href="https://techhub.social/tags/reserve" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>reserve</span></a> <a href="https://techhub.social/tags/ecogeography" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ecogeography</span></a> <a href="https://techhub.social/tags/geography" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>geography</span></a> <a href="https://techhub.social/tags/factors" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>factors</span></a> <a href="https://techhub.social/tags/parameters" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>parameters</span></a> <a href="https://techhub.social/tags/drivers" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>drivers</span></a> <a href="https://techhub.social/tags/temperature" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>temperature</span></a> <a href="https://techhub.social/tags/precipitation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>precipitation</span></a> <a href="https://techhub.social/tags/rainfall" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>rainfall</span></a> <a href="https://techhub.social/tags/model" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>model</span></a> <a href="https://techhub.social/tags/modeling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>modeling</span></a> <a href="https://techhub.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a> <a href="https://techhub.social/tags/framework" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>framework</span></a> <a href="https://techhub.social/tags/slope" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>slope</span></a> <a href="https://techhub.social/tags/water" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>water</span></a> <a href="https://techhub.social/tags/hydrology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hydrology</span></a> <a href="https://techhub.social/tags/infrastructure" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>infrastructure</span></a> <a href="https://techhub.social/tags/mitigation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mitigation</span></a> <a href="https://techhub.social/tags/monitoring" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>monitoring</span></a> <a href="https://techhub.social/tags/preparedness" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>preparedness</span></a> <a href="https://techhub.social/tags/forestfires" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>forestfires</span></a></p>
Paul Healey<p><a href="https://open.substack.com/pub/thefuckingnews/p/real-trump-losing-in-the-polls-to?r=29jpsy&amp;utm_medium=ios" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">open.substack.com/pub/thefucki</span><span class="invisible">ngnews/p/real-trump-losing-in-the-polls-to?r=29jpsy&amp;utm_medium=ios</span></a> <a href="https://universeodon.com/tags/MagicalTrump" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MagicalTrump</span></a> <a href="https://universeodon.com/tags/RealTrump" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RealTrump</span></a>, so all you get with the <a href="https://universeodon.com/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> factor is reality without the navigator, just the chaos; the illusion of randomness, the collapse and the sinking? An Emperor is no Deity, no constitution of the categories foundation, just an aimless clown deluded by the opium of his cult and the grandeur of its Nazi oligarchs. <a href="https://universeodon.com/tags/Poll" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Poll</span></a> <a href="https://universeodon.com/tags/Polls" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Polls</span></a> <a href="https://universeodon.com/tags/NaziOligarchs" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>NaziOligarchs</span></a> <a href="https://universeodon.com/tags/GreatLiars" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GreatLiars</span></a></p>
Dr Mircea Zloteanu 🌼🐝<p><a href="https://mastodon.social/tags/statstab" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statstab</span></a> #329 Bayesian versus frequentist approaches in multilevel single-case designs: on power and type I error rate</p><p>Thoughts: An interesting project highlighting some benefits of <a href="https://mastodon.social/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a> methods for <a href="https://mastodon.social/tags/nof1" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>nof1</span></a> designs.</p><p><a href="https://mastodon.social/tags/stats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>stats</span></a> <a href="https://mastodon.social/tags/r" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>r</span></a> <a href="https://mastodon.social/tags/sced" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>sced</span></a> <a href="https://mastodon.social/tags/mixedeffects" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mixedeffects</span></a></p><p><a href="https://osf.io/k7b82/files/osfstorage" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">osf.io/k7b82/files/osfstorage</span><span class="invisible"></span></a></p>
💧🌏 Greg Cocks<p>Observations Reveal Changing Coastal Storm Extremes Around The United States<br>--<br><a href="https://doi.org/10.1038/s41558-025-02315-z" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1038/s41558-025-023</span><span class="invisible">15-z</span></a> &lt;-- shared paper<br>--<br><a href="https://techhub.social/tags/GIS" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GIS</span></a> <a href="https://techhub.social/tags/spatial" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatial</span></a> <a href="https://techhub.social/tags/mapping" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mapping</span></a> <a href="https://techhub.social/tags/extremeweather" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>extremeweather</span></a> <a href="https://techhub.social/tags/coast" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>coast</span></a> <a href="https://techhub.social/tags/coastal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>coastal</span></a> <a href="https://techhub.social/tags/spatialanalysis" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatialanalysis</span></a> <a href="https://techhub.social/tags/spatiotemporal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>spatiotemporal</span></a> <a href="https://techhub.social/tags/model" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>model</span></a> <a href="https://techhub.social/tags/modeling" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>modeling</span></a> <a href="https://techhub.social/tags/communities" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>communities</span></a> <a href="https://techhub.social/tags/publicsafety" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>publicsafety</span></a> <a href="https://techhub.social/tags/climatechange" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>climatechange</span></a> <a href="https://techhub.social/tags/stormsurge" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>stormsurge</span></a> <a href="https://techhub.social/tags/USA" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>USA</span></a> <a href="https://techhub.social/tags/flood" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>flood</span></a> <a href="https://techhub.social/tags/flooding" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>flooding</span></a> <a href="https://techhub.social/tags/risk" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>risk</span></a> <a href="https://techhub.social/tags/hazard" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hazard</span></a> <a href="https://techhub.social/tags/damage" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>damage</span></a> <a href="https://techhub.social/tags/infrastructure" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>infrastructure</span></a> <a href="https://techhub.social/tags/cost" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>cost</span></a> <a href="https://techhub.social/tags/economics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>economics</span></a> <a href="https://techhub.social/tags/mitigation" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>mitigation</span></a> <a href="https://techhub.social/tags/insurance" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>insurance</span></a> <a href="https://techhub.social/tags/sealevel" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>sealevel</span></a> <a href="https://techhub.social/tags/SLR" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>SLR</span></a> <a href="https://techhub.social/tags/sealevelrise" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>sealevelrise</span></a> <a href="https://techhub.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://techhub.social/tags/hierarchical" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hierarchical</span></a> <a href="https://techhub.social/tags/framework" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>framework</span></a> <a href="https://techhub.social/tags/tideguage" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tideguage</span></a> <a href="https://techhub.social/tags/tide" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tide</span></a> <a href="https://techhub.social/tags/tidal" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>tidal</span></a> <a href="https://techhub.social/tags/water" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>water</span></a> <a href="https://techhub.social/tags/hydrology" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hydrology</span></a> <a href="https://techhub.social/tags/hydrography" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>hydrography</span></a> <a href="https://techhub.social/tags/extremes" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>extremes</span></a> <a href="https://techhub.social/tags/intensity" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>intensity</span></a> <a href="https://techhub.social/tags/monitoring" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>monitoring</span></a></p>
Steven<p>Hot off the press - our report on gender disparities in grant seeking at the University of Cambridge (who applies for and who gets research grant funding). </p><p><a href="https://www.bennettinstitute.cam.ac.uk/publications/improving-inclusivity-in-grant-funding-initial-gender-analysis/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">bennettinstitute.cam.ac.uk/pub</span><span class="invisible">lications/improving-inclusivity-in-grant-funding-initial-gender-analysis/</span></a></p><p>The story: <br>1) The structural disparities are big (not so surprising)<br>2) The patterns of disparity at particular grades in particular disciplines go both ways (more surprising)</p><p><a href="https://fosstodon.org/tags/ResearchPolicy" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ResearchPolicy</span></a><br><a href="https://fosstodon.org/tags/ResearchGrants" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ResearchGrants</span></a><br><a href="https://fosstodon.org/tags/GenderDifferences" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GenderDifferences</span></a><br><a href="https://fosstodon.org/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a></p><p>If you like graphs, you'll probably like it!</p><p><a href="https://fosstodon.org/tags/RandomCambridgeWindowPicture" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RandomCambridgeWindowPicture</span></a></p>
PyMC developers<p>PyMC is in Google Summer of Code 2025!</p><p>We're excited to be part of <a href="https://bayes.club/tags/GSoC2025" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>GSoC2025</span></a> under <span class="h-card" translate="no"><a href="https://mastodon.social/@NumFOCUS" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>NumFOCUS</span></a></span> If you're passionate about <a href="https://bayes.club/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> stats &amp; <a href="https://bayes.club/tags/OpenSource" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>OpenSource</span></a>, this is your chance to contribute to <a href="https://bayes.club/tags/PyMC" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>PyMC</span></a>!</p><p>📅 Deadline: April 8, 18:00 UTC<br>🔗 Apply now: <a href="https://www.pymc.io/blog/blog_gsoc_2025_announcement.html" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">pymc.io/blog/blog_gsoc_2025_an</span><span class="invisible">nouncement.html</span></a></p>
pglpm<p><span class="h-card" translate="no"><a href="https://fosstodon.org/@Posit" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>Posit</span></a></span> </p><p>It's important to emphasize that "realistic-looking" data does *not* mean "realistic" data – especially high-dimensional data (unfortunately that post doesn't warn against this).</p><p>If one had an algorithm that generated realistic data for a given inference problem, it would mean that that inference problem had been solved. So: for educational purposes, why not. But for validation-like purposes, use with uttermost caution and at your own peril.</p><p><a href="https://c.im/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>rstats</span></a> <a href="https://c.im/tags/statistics" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>statistics</span></a> <a href="https://c.im/tags/bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>bayesian</span></a></p>
Jakub Nowosad<p>The bayesEO package provides a Bayesian approach to post-processing ML-generated images. It refines class probabilities, removes outliers, and improves labeling for more accurate classification.</p><p>🔗 <a href="https://github.com/e-sensing/bayesEO/" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">github.com/e-sensing/bayesEO/</span><span class="invisible"></span></a> </p><p><a href="https://fosstodon.org/tags/rstats" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>rstats</span></a> <a href="https://fosstodon.org/tags/MachineLearning" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>MachineLearning</span></a> <a href="https://fosstodon.org/tags/RemoteSensing" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>RemoteSensing</span></a> <a href="https://fosstodon.org/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> <a href="https://fosstodon.org/tags/rspatial" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>rspatial</span></a></p>
Manuel Baltieri<p>After a long collaboration with <span class="h-card" translate="no"><a href="https://mathstodon.xyz/@martinbiehl" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>martinbiehl</span></a></span>, <span class="h-card" translate="no"><a href="https://mathstodon.xyz/@mc" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>mc</span></a></span> and <span class="h-card" translate="no"><a href="https://mathstodon.xyz/@Nathaniel" class="u-url mention" rel="nofollow noopener noreferrer" target="_blank">@<span>Nathaniel</span></a></span> I’m excited to share the first of (hopefully) many outputs:<br>“A Bayesian Interpretation of the Internal Model Principle”<br><a href="https://arxiv.org/abs/2503.00511" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2503.00511</span><span class="invisible"></span></a>.</p><p>This work combines ideas from control theory, applied <a href="https://mathstodon.xyz/tags/categorytheory" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>categorytheory</span></a> and <a href="https://mathstodon.xyz/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> reasoning, with ramifications for <a href="https://mathstodon.xyz/tags/cognitive" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>cognitive</span></a> science, <a href="https://mathstodon.xyz/tags/AI" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>AI</span></a>/#ML, <a href="https://mathstodon.xyz/tags/ALife" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>ALife</span></a> and biology to be further explored in the future.</p><p>In these fields, we come across ideas of “models”, “internal models”, “world models”, etc. but it is hard to find formal definitions, and when one does, they usually aren’t general enough to cover all the aspects these different fields consider important.</p><p>In this work, we focus on two specific definitions of models, and show their connections. One is inspired by work in control theory, and one comes from Bayesian inference/filtering for cognitive science, AI and ALife, and is formalised with Markov categories.</p><p>In the first part, we review and reformulate the “internal model principle” from control theory (at least, one of its versions) in a more modern language heavily inspired by categorical systems theory (<a href="https://www.davidjaz.com/Papers/DynamicalBook.pdf" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">davidjaz.com/Papers/DynamicalB</span><span class="invisible">ook.pdf</span></a>, <a href="https://github.com/mattecapu/categorical-systems-theory/blob/master/main.pdf" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">github.com/mattecapu/categoric</span><span class="invisible">al-systems-theory/blob/master/main.pdf</span></a>).</p>
Francisco Rodriguez-Sanchez<p>6/ Thus we built upon this <a href="https://ecoevo.social/tags/Bayesian" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>Bayesian</span></a> framework (<a href="https://doi.org/10.1038/s41467-021-24149-x" rel="nofollow noopener noreferrer" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1038/s41467-021-241</span><span class="invisible">49-x</span></a>) to infer each pairwise interaction in individual-based <a href="https://ecoevo.social/tags/networks" class="mention hashtag" rel="nofollow noopener noreferrer" target="_blank">#<span>networks</span></a> accounting for sampling effort and the inherent stochasticity of field data</p>
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