<?xml version="1.0" encoding="utf-8"?><feed xmlns="http://www.w3.org/2005/Atom" ><generator uri="https://jekyllrb.com/" version="3.10.0">Jekyll</generator><link href="https://proceedings.mlr.press/v327/feed.xml" rel="self" type="application/atom+xml" /><link href="https://proceedings.mlr.press/v327/" rel="alternate" type="text/html" /><updated>2026-09-11T06:57:54+00:00</updated><id>https://proceedings.mlr.press/v327/feed.xml</id><title type="html">Proceedings of Machine Learning Research</title><subtitle>Proceedings of The 1st Symposium on Probabilistic Machine Learning
  Held in Korea Institute for Advanced Study, Seoul, South Korea on 05 July 2026

Published as Volume 327 by the Proceedings of Machine Learning Research on 11 September 2026.

Volume Edited by:
  Siddharth Swaroop
  David Rügamer
  Agustinus Kristiadi

Series Editors:
  Tegan Emerson
  Hoel Kervadec
  Neil D. Lawrence
</subtitle><author><name>PMLR</name></author><entry><title type="html">Latent Semantic Regularization: Enhancing Semantic Integrity in Tabular Data Synthesis</title><link href="https://proceedings.mlr.press/v327/amiri26a.html" rel="alternate" type="text/html" title="Latent Semantic Regularization: Enhancing Semantic Integrity in Tabular Data Synthesis" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/amiri26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/amiri26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Saba&quot;, &quot;family&quot;=&gt;&quot;Amiri&quot;}, {&quot;given&quot;=&gt;&quot;Carlijn&quot;, &quot;family&quot;=&gt;&quot;Nijhuis&quot;}, {&quot;given&quot;=&gt;&quot;Eric&quot;, &quot;family&quot;=&gt;&quot;Nalisnick&quot;}, {&quot;given&quot;=&gt;&quot;Adam&quot;, &quot;family&quot;=&gt;&quot;Belloum&quot;}, {&quot;given&quot;=&gt;&quot;Sander&quot;, &quot;family&quot;=&gt;&quot;Klous&quot;}, {&quot;given&quot;=&gt;&quot;Leon&quot;, &quot;family&quot;=&gt;&quot;Gommans&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Conditionally Identifiable Latent Representation for Multivariate Time Series with Structural Dynamics</title><link href="https://proceedings.mlr.press/v327/chang26a.html" rel="alternate" type="text/html" title="Conditionally Identifiable Latent Representation for Multivariate Time Series with Structural Dynamics" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/chang26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/chang26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Minkey&quot;, &quot;family&quot;=&gt;&quot;Chang&quot;}, {&quot;given&quot;=&gt;&quot;Jae-Young&quot;, &quot;family&quot;=&gt;&quot;Kim&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">RAMP: Recognition parametrisation by Amortised Message Passing</title><link href="https://proceedings.mlr.press/v327/fox26a.html" rel="alternate" type="text/html" title="RAMP: Recognition parametrisation by Amortised Message Passing" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/fox26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/fox26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Lior&quot;, &quot;family&quot;=&gt;&quot;Fox&quot;}, {&quot;given&quot;=&gt;&quot;Kai&quot;, &quot;family&quot;=&gt;&quot;Biegun&quot;}, {&quot;given&quot;=&gt;&quot;James&quot;, &quot;family&quot;=&gt;&quot;Heald&quot;}, {&quot;given&quot;=&gt;&quot;Samo&quot;, &quot;family&quot;=&gt;&quot;Hromadka&quot;}, {&quot;given&quot;=&gt;&quot;Arielle&quot;, &quot;family&quot;=&gt;&quot;Rosinski&quot;}, {&quot;given&quot;=&gt;&quot;Maneesh&quot;, &quot;family&quot;=&gt;&quot;Sahani&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms</title><link href="https://proceedings.mlr.press/v327/grunefeld26a.html" rel="alternate" type="text/html" title="An Isotropic Approach to Efficient Uncertainty Quantification with Gradient Norms" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/grunefeld26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/grunefeld26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Nils&quot;, &quot;family&quot;=&gt;&quot;Grünefeld&quot;}, {&quot;given&quot;=&gt;&quot;Jes&quot;, &quot;family&quot;=&gt;&quot;Frellsen&quot;}, {&quot;given&quot;=&gt;&quot;Christian&quot;, &quot;family&quot;=&gt;&quot;Hardmeier&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Uncertainty Propagation Through Green’s Kernels and Gaussian Process Inference Dynamics</title><link href="https://proceedings.mlr.press/v327/lo26a.html" rel="alternate" type="text/html" title="Uncertainty Propagation Through Green’s Kernels and Gaussian Process Inference Dynamics" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/lo26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/lo26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Chi-Jen Roger&quot;, &quot;family&quot;=&gt;&quot;Lo&quot;}, {&quot;given&quot;=&gt;&quot;Joan&quot;, &quot;family&quot;=&gt;&quot;Lasenby&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Neural Stochastic Differential Equations on Compact State Spaces: Theory, Methods, and Application to Suicide Risk Modeling</title><link href="https://proceedings.mlr.press/v327/lu26a.html" rel="alternate" type="text/html" title="Neural Stochastic Differential Equations on Compact State Spaces: Theory, Methods, and Application to Suicide Risk Modeling" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/lu26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/lu26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Malinda&quot;, &quot;family&quot;=&gt;&quot;Lu&quot;}, {&quot;given&quot;=&gt;&quot;Yue-Jane&quot;, &quot;family&quot;=&gt;&quot;Liu&quot;}, {&quot;given&quot;=&gt;&quot;Matthew K.&quot;, &quot;family&quot;=&gt;&quot;Nock&quot;}, {&quot;given&quot;=&gt;&quot;Yaniv&quot;, &quot;family&quot;=&gt;&quot;Yacoby&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Intention Inference Under Execution Noise: Separating Aleatoric and Epistemic Uncertainty in Social Dilemmas</title><link href="https://proceedings.mlr.press/v327/mahadew26a.html" rel="alternate" type="text/html" title="Intention Inference Under Execution Noise: Separating Aleatoric and Epistemic Uncertainty in Social Dilemmas" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/mahadew26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/mahadew26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Kival&quot;, &quot;family&quot;=&gt;&quot;Mahadew&quot;}, {&quot;given&quot;=&gt;&quot;Jonathan P.&quot;, &quot;family&quot;=&gt;&quot;Shock&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Causal Temporal Graphs for Counterfactual Validation of Temporal Link Prediction</title><link href="https://proceedings.mlr.press/v327/rahman26a.html" rel="alternate" type="text/html" title="Causal Temporal Graphs for Counterfactual Validation of Temporal Link Prediction" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/rahman26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/rahman26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Aniq Ur&quot;, &quot;family&quot;=&gt;&quot;Rahman&quot;}, {&quot;given&quot;=&gt;&quot;Justin&quot;, &quot;family&quot;=&gt;&quot;Coon&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Universality of Singular Complexity for Hyvärinen Generalized Bayes: Exact Transfer in Gaussian Factor Analysis</title><link href="https://proceedings.mlr.press/v327/saravanan26a.html" rel="alternate" type="text/html" title="Universality of Singular Complexity for Hyvärinen Generalized Bayes: Exact Transfer in Gaussian Factor Analysis" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/saravanan26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/saravanan26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Manoj&quot;, &quot;family&quot;=&gt;&quot;Saravanan&quot;}, {&quot;given&quot;=&gt;&quot;Rohit Kumar&quot;, &quot;family&quot;=&gt;&quot;Salla&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry><entry><title type="html">Anchor-Based Heteroscedastic Noise for Preferential Bayesian Optimization</title><link href="https://proceedings.mlr.press/v327/sinaga26a.html" rel="alternate" type="text/html" title="Anchor-Based Heteroscedastic Noise for Preferential Bayesian Optimization" /><published>2026-09-11T00:00:00+00:00</published><updated>2026-09-11T00:00:00+00:00</updated><id>https://proceedings.mlr.press/v327/sinaga26a</id><content type="html" xml:base="https://proceedings.mlr.press/v327/sinaga26a.html"><![CDATA[]]></content><author><name>[{&quot;given&quot;=&gt;&quot;Marshal Arijona&quot;, &quot;family&quot;=&gt;&quot;Sinaga&quot;}, {&quot;given&quot;=&gt;&quot;Julien&quot;, &quot;family&quot;=&gt;&quot;Martinelli&quot;}, {&quot;given&quot;=&gt;&quot;Samuel&quot;, &quot;family&quot;=&gt;&quot;Kaski&quot;}]</name></author><summary type="html"><![CDATA[]]></summary></entry></feed>