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      <title>Generative AI: Old and New</title>
      <link>https://generativeai-old-and-new.github.io</link>
      <description>Last 10 notes on Generative AI: Old and New</description>
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    <title>Module 2: Deep Learning Basics</title>
    <link>https://generativeai-old-and-new.github.io/modules/02-deep-learning-basics</link>
    <guid>https://generativeai-old-and-new.github.io/modules/02-deep-learning-basics</guid>
    <description><![CDATA[ Optimization and neural network basics for generative modeling. ]]></description>
    <pubDate>Fri, 05 Jun 2026 03:00:58 GMT</pubDate>
  </item><item>
    <title>Module 7: Language Models</title>
    <link>https://generativeai-old-and-new.github.io/modules/07-language-models</link>
    <guid>https://generativeai-old-and-new.github.io/modules/07-language-models</guid>
    <description><![CDATA[ Autoregressive language models and GPT-style next-token prediction. ]]></description>
    <pubDate>Fri, 05 Jun 2026 01:37:49 GMT</pubDate>
  </item><item>
    <title>Module 5: Autoencoder Models</title>
    <link>https://generativeai-old-and-new.github.io/modules/05-autoencoder-models</link>
    <guid>https://generativeai-old-and-new.github.io/modules/05-autoencoder-models</guid>
    <description><![CDATA[ Autoencoders, adversarial autoencoders, VAEs, ELBOs, and latent variable modeling. ]]></description>
    <pubDate>Thu, 04 Jun 2026 23:42:42 GMT</pubDate>
  </item><item>
    <title>Module 1: Probability Basics</title>
    <link>https://generativeai-old-and-new.github.io/modules/01-probability-basics</link>
    <guid>https://generativeai-old-and-new.github.io/modules/01-probability-basics</guid>
    <description><![CDATA[ Probability basics, distribution learning, KL divergence, and maximum likelihood estimation. ]]></description>
    <pubDate>Sat, 30 May 2026 22:25:12 GMT</pubDate>
  </item><item>
    <title>Homework 1: Probability and MLE</title>
    <link>https://generativeai-old-and-new.github.io/homework/01-probability-basics</link>
    <guid>https://generativeai-old-and-new.github.io/homework/01-probability-basics</guid>
    <description><![CDATA[ Homework problems for Module 1 covering Gaussian identities, KL divergence, categorical MLE, and energy-based models. ]]></description>
    <pubDate>Sat, 30 May 2026 21:47:34 GMT</pubDate>
  </item><item>
    <title>Homework 2: Optimization and Neural Networks</title>
    <link>https://generativeai-old-and-new.github.io/homework/02-optimization</link>
    <guid>https://generativeai-old-and-new.github.io/homework/02-optimization</guid>
    <description><![CDATA[ Homework problems for Module 2 covering gradient descent, optimizer behavior, nonconvex landscapes, and MLP training. ]]></description>
    <pubDate>Sat, 30 May 2026 21:47:34 GMT</pubDate>
  </item><item>
    <title>Homework</title>
    <link>https://generativeai-old-and-new.github.io/homework/</link>
    <guid>https://generativeai-old-and-new.github.io/homework/</guid>
    <description><![CDATA[ Homework pages for Generative AI: Old and New. ]]></description>
    <pubDate>Sat, 30 May 2026 21:47:34 GMT</pubDate>
  </item><item>
    <title>Generative AI: Old and New</title>
    <link>https://generativeai-old-and-new.github.io/</link>
    <guid>https://generativeai-old-and-new.github.io/</guid>
    <description><![CDATA[ Course notes on generative modeling. ]]></description>
    <pubDate>Sat, 30 May 2026 02:36:24 GMT</pubDate>
  </item><item>
    <title>Module 3: Invertible Models</title>
    <link>https://generativeai-old-and-new.github.io/modules/03-invertible-models</link>
    <guid>https://generativeai-old-and-new.github.io/modules/03-invertible-models</guid>
    <description><![CDATA[ Invertible models, normalizing flows, likelihoods, and practical flow architectures. ]]></description>
    <pubDate>Thu, 28 May 2026 03:37:32 GMT</pubDate>
  </item><item>
    <title>Module 4: Generative Adversarial Networks</title>
    <link>https://generativeai-old-and-new.github.io/modules/04-generative-adversarial-networks</link>
    <guid>https://generativeai-old-and-new.github.io/modules/04-generative-adversarial-networks</guid>
    <description><![CDATA[ GANs, likelihood-free training, IPMs, regularization, and minimax optimization. ]]></description>
    <pubDate>Thu, 28 May 2026 03:37:32 GMT</pubDate>
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