<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Bayesian Inference |</title><link>https://cnardin.github.io/it/tags/bayesian-inference/</link><atom:link href="https://cnardin.github.io/it/tags/bayesian-inference/index.xml" rel="self" type="application/rss+xml"/><description>Bayesian Inference</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>it-it</language><lastBuildDate>Fri, 24 Jul 2026 00:00:00 +0000</lastBuildDate><image><url>https://cnardin.github.io/media/icon_hu_2d2b1e39e19355d7.png</url><title>Bayesian Inference</title><link>https://cnardin.github.io/it/tags/bayesian-inference/</link></image><item><title>WCCM-ECCOMAS 2026 — World Congress on Computational Mechanics</title><link>https://cnardin.github.io/it/news/2026-wccm-reactis/</link><pubDate>Fri, 24 Jul 2026 00:00:00 +0000</pubDate><guid>https://cnardin.github.io/it/news/2026-wccm-reactis/</guid><description>
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&lt;div class="callout-title font-semibold mb-1"&gt;WCCM-ECCOMAS 2026&lt;/div&gt;
&lt;div class="callout-body"&gt;&lt;p&gt;World Congress on Computational Mechanics — ECCOMAS Congress 2026.
Monaco di Baviera, Germania — &lt;strong&gt;19–24 luglio 2026&lt;/strong&gt;.&lt;/p&gt;&lt;/div&gt;
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&lt;p&gt;Una settimana molto intensa con la RSUQ Chair a &lt;strong&gt;WCCM-ECCOMAS 2026&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;Il congresso è stato un&amp;rsquo;occasione unica per presentare le nostre ricerche più recenti all&amp;rsquo;incrocio tra &lt;strong&gt;quantificazione dell&amp;rsquo;incertezza, affidabilità, modellazione stocastica, inferenza bayesiana e meccanica computazionale&lt;/strong&gt;. Siamo stati orgogliosi di contribuire con cinque presentazioni su diversi aspetti del nostro lavoro.&lt;/p&gt;
&lt;h2 id="contributi"&gt;Contributi&lt;/h2&gt;
&lt;p&gt;🔹 &lt;strong&gt;S. Marelli, S. Schär, C. Nardin &amp;amp; B. Sudret&lt;/strong&gt; — &lt;em&gt;Reliability analysis on dynamical systems using manifold-autoregressive surrogate models&lt;/em&gt;
La keynote di Stefano ha presentato &lt;strong&gt;mNARX+&lt;/strong&gt;, un framework basato sui dati per modellare sistemi dinamici complessi con stati interni e danneggiamento in evoluzione, che permette un&amp;rsquo;analisi di affidabilità efficiente di sistemi con comportamento non stazionario.&lt;/p&gt;
&lt;p&gt;🔹 &lt;strong&gt;C. Nardin, S. Marelli, M. Broccardo &amp;amp; B. Sudret&lt;/strong&gt; — &lt;em&gt;A Continuous Markov-Chain Perspective on Joint Seismic Reliability and Resilience Assessment&lt;/em&gt;
In questo lavoro ho introdotto le &lt;strong&gt;catene di Markov a tempo continuo&lt;/strong&gt; nel framework PEER-PBEE, offrendo una prospettiva unitaria per modellare sia il danneggiamento sia i processi di ripristino e per valutare in modo coerente affidabilità e resilienza sismica.&lt;/p&gt;
&lt;p&gt;🔹 &lt;strong&gt;A. Herr, S. Marelli &amp;amp; B. Sudret&lt;/strong&gt; — &lt;em&gt;Introducing Stochastic Emulators for Hierarchical Bayesian Inference of Population Parameters&lt;/em&gt;
Anna ha presentato un nuovo approccio basato su &lt;strong&gt;emulatori stocastici&lt;/strong&gt; che approssima direttamente le risposte a livello di popolazione, riducendo il costo computazionale dell&amp;rsquo;inferenza bayesiana gerarchica per modelli costosi e stocastici.&lt;/p&gt;
&lt;p&gt;🔹 &lt;strong&gt;S. Marelli, S. Schär &amp;amp; B. Sudret&lt;/strong&gt; — &lt;em&gt;UQLab – An Open-Source Tool for Uncertainty Quantification with Dynamical Systems&lt;/em&gt;
Stefano ha illustrato le funzionalità più recenti di &lt;strong&gt;UQLab&lt;/strong&gt;, tra cui il supporto a serie temporali, sistemi dinamici e metamodelli avanzati basati sui dati come &lt;strong&gt;PC-NARX, F-NARX e mNARX+&lt;/strong&gt;.&lt;/p&gt;
&lt;p&gt;🔹 &lt;strong&gt;Moustapha&lt;/strong&gt; — &lt;em&gt;Reliability-Based Design Optimization with Stochastic Emulators&lt;/em&gt;
Il lavoro di Moustapha sulla &lt;strong&gt;RBDO&lt;/strong&gt; ha mostrato come gli emulatori stocastici possano essere un&amp;rsquo;alternativa efficiente ai classici metamodelli deterministici, in particolare per spazi di incertezza ad alta dimensione e simulatori intrinsecamente stocastici.&lt;/p&gt;
&lt;p&gt;Nel loro insieme, questi contributi riflettono la visione di ricerca della Chair: sviluppare metodi computazionali efficienti, scalabili e affidabili per la quantificazione dell&amp;rsquo;incertezza e per decisioni informate sul rischio, collegando gli sviluppi metodologici di base ad applicazioni ingegneristiche impegnative.&lt;/p&gt;
&lt;p&gt;Complimenti a tutti gli autori e relatori per l&amp;rsquo;ottimo lavoro, e grazie agli organizzatori di &lt;strong&gt;WCCM-ECCOMAS 2026&lt;/strong&gt; per aver riunito una comunità scientifica così vivace. È stato un piacere incontrare colleghi vecchi e nuovi, discutere nuove idee e vedere le comunità della UQ e della meccanica computazionale riunite in un congresso così grande.&lt;/p&gt;
&lt;h2 id="abstract"&gt;Abstract&lt;/h2&gt;
&lt;p&gt;C. Nardin, S. Marelli, M. Broccardo &amp;amp; B. Sudret —
&lt;strong&gt;A Continuous Markov-Chain Perspective on Joint Seismic Reliability and Resilience Assessment&lt;/strong&gt;
&lt;em&gt;WCCM-ECCOMAS 2026&lt;/em&gt;, Monaco di Baviera, luglio 2026.&lt;/p&gt;
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&lt;em&gt;La RSUQ Chair a WCCM-ECCOMAS 2026, Monaco di Baviera — luglio 2026.&lt;/em&gt;&lt;/p&gt;</description></item><item><title>Bay-Fi: Approximate Bayesian main Frequency Identification for extremely undersampled signals</title><link>https://cnardin.github.io/it/publication/articles/2026-mssp-bayfi/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://cnardin.github.io/it/publication/articles/2026-mssp-bayfi/</guid><description>
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&lt;div class="callout-title font-semibold mb-1"&gt;Suggerimento&lt;/div&gt;
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&lt;/div&gt;</description></item><item><title>Bayesian Approach for Main Frequency Identification on Extremely Under-Sampled Signals</title><link>https://cnardin.github.io/it/publication/conferences/2025-evaces-bayfi/</link><pubDate>Wed, 02 Jul 2025 00:00:00 +0000</pubDate><guid>https://cnardin.github.io/it/publication/conferences/2025-evaces-bayfi/</guid><description>
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