<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Generative AI | Baris Sarper Tezcan</title><link>https://barissarpertezcan.github.io/tags/generative-ai/</link><atom:link href="https://barissarpertezcan.github.io/tags/generative-ai/index.xml" rel="self" type="application/rss+xml"/><description>Generative AI</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 20 Jun 2024 00:00:00 +0000</lastBuildDate><image><url>https://barissarpertezcan.github.io/media/logo.svg</url><title>Generative AI</title><link>https://barissarpertezcan.github.io/tags/generative-ai/</link></image><item><title>ICCV 2023 Paper Implementation DiffDis – Deep Generative Models Course</title><link>https://barissarpertezcan.github.io/project/diffdis/</link><pubDate>Thu, 20 Jun 2024 00:00:00 +0000</pubDate><guid>https://barissarpertezcan.github.io/project/diffdis/</guid><description>&lt;p>Implemented &lt;a href="https://openaccess.thecvf.com/content/ICCV2023/papers/Huang_DiffDis_Empowering_Generative_Diffusion_Model_with_Cross-Modal_Discrimination_Capability_ICCV_2023_paper.pdf" target="_blank" rel="noopener noreferrer">&amp;ldquo;DiffDis: Empowering Generative Diffusion Model with Cross-Modal Discrimination Capability&amp;rdquo; (ICCV 2023)&lt;/a> as the project of the Deep Generative Models course. Developed a working version of the paper, addressing the lack of open-source implementation.&lt;/p></description></item></channel></rss>