<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Machine Learning | Keita Itano - Academic Portfolio</title><link>https://keitaitano.github.io/portfolio/tags/machine-learning/</link><atom:link href="https://keitaitano.github.io/portfolio/tags/machine-learning/index.xml" rel="self" type="application/rss+xml"/><description>Machine Learning</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Mon, 31 Mar 2025 00:00:00 +0000</lastBuildDate><image><url>https://keitaitano.github.io/portfolio/media/icon_hu_48576da7a607172d.png</url><title>Machine Learning</title><link>https://keitaitano.github.io/portfolio/tags/machine-learning/</link></image><item><title>Evaluation of Matrix Effects in SIMS Using Gaussian Process Regression: The Case of Olivine Mg Isotope Microanalysis</title><link>https://keitaitano.github.io/portfolio/publications/rcms2025/</link><pubDate>Mon, 31 Mar 2025 00:00:00 +0000</pubDate><guid>https://keitaitano.github.io/portfolio/publications/rcms2025/</guid><description>&lt;h3 id="key-highlights"&gt;Key Highlights&lt;/h3&gt;
&lt;ul&gt;
&lt;li&gt;&lt;strong&gt;Uncertainty Quantification:&lt;/strong&gt; Demonstrates the application of Gaussian process regression (GPR) to correct SIMS matrix effects while providing quantitative prediction uncertainties.&lt;/li&gt;
&lt;li&gt;&lt;strong&gt;Minor Element Impact:&lt;/strong&gt; Reveals that minor elements in olivine (Ca, Cr, Mn) independently impact instrumental mass fractionation (IMF) during SIMS Mg isotope analysis.&lt;/li&gt;
&lt;/ul&gt;</description></item></channel></rss>