<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Quantum machine learning | Giovanni Scala | Quantum Information</title><link>https://giovanniscala.github.io/tag/quantum-machine-learning/</link><atom:link href="https://giovanniscala.github.io/tag/quantum-machine-learning/index.xml" rel="self" type="application/rss+xml"/><description>Quantum machine learning</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><copyright>© 2026 Giovanni Scala</copyright><lastBuildDate>Mon, 14 Sep 2026 00:00:00 +0000</lastBuildDate><image><url>https://giovanniscala.github.io/media/icon_hub9af10373a867da90b39ee3f3796e0ee_26097_512x512_fill_lanczos_center_2.png</url><title>Quantum machine learning</title><link>https://giovanniscala.github.io/tag/quantum-machine-learning/</link></image><item><title>Quantum Machine Learning</title><link>https://giovanniscala.github.io/project/quantum-machine-learning/</link><pubDate>Mon, 14 Sep 2026 00:00:00 +0000</pubDate><guid>https://giovanniscala.github.io/project/quantum-machine-learning/</guid><description>&lt;p>This research investigates when quantum-data kernels remain informative with finite measurement budgets, with emphasis on resource scaling, concentration effects, and quantum phase-transition learning.&lt;/p></description></item><item><title>Finite-size resource scaling for learning quantum phase transitions with fidelity-based support vector machines</title><link>https://giovanniscala.github.io/publication/2026/finite-size-resource-scaling-qml/</link><pubDate>Thu, 19 Mar 2026 00:00:00 +0000</pubDate><guid>https://giovanniscala.github.io/publication/2026/finite-size-resource-scaling-qml/</guid><description/></item></channel></rss>