<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Boukani, A. | PACS Lab</title><link>https://pacslab.github.io/author/boukani-a./</link><atom:link href="https://pacslab.github.io/author/boukani-a./index.xml" rel="self" type="application/rss+xml"/><description>Boukani, A.</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Wed, 01 Jan 2025 00:00:00 +0000</lastBuildDate><image><url>https://pacslab.github.io/media/logo_hu_68bd2091955c32d2.png</url><title>Boukani, A.</title><link>https://pacslab.github.io/author/boukani-a./</link></image><item><title>CAPE: Generalized Convergence Prediction Across Architectures Without Full Training</title><link>https://pacslab.github.io/publication/2025-cape-generalized-convergence-prediction-across-architec/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://pacslab.github.io/publication/2025-cape-generalized-convergence-prediction-across-architec/</guid><description/></item><item><title>PreNeT: Leveraging Computational Features to Predict Deep Neural Network Training Time</title><link>https://pacslab.github.io/publication/2025-prenet-leveraging-computational-features-to-predict-dee/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://pacslab.github.io/publication/2025-prenet-leveraging-computational-features-to-predict-dee/</guid><description/></item></channel></rss>