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      <title>Hovhannes Grigoryan</title>
      <link>https://iohanngrig.github.io</link>
      <description>Last 10 notes on Hovhannes Grigoryan</description>
      <generator>Quartz -- quartz.jzhao.xyz</generator>
      <item>
    <title>About</title>
    <link>https://iohanngrig.github.io/about</link>
    <guid>https://iohanngrig.github.io/about</guid>
    <description><![CDATA[ About I am a Senior Applied Scientist at Amazon in New York City, working on causal inference, mechanism design, and agentic AI for large-scale decision systems. ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
  </item><item>
    <title>Applications</title>
    <link>https://iohanngrig.github.io/applications/</link>
    <guid>https://iohanngrig.github.io/applications/</guid>
    <description><![CDATA[ Applications Small, self-contained demos of analytical methods applied to financial and statistical problems. ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
  </item><item>
    <title>Hovhannes Grigoryan</title>
    <link>https://iohanngrig.github.io/</link>
    <guid>https://iohanngrig.github.io/</guid>
    <description><![CDATA[ Hovhannes Grigoryan Causal identification and mechanism design for agent-driven decision systems. ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
  </item><item>
    <title>Chapter 1 · Gödel, Löb, and self-referential AI</title>
    <link>https://iohanngrig.github.io/lectures/agi-foundations/ch1</link>
    <guid>https://iohanngrig.github.io/lectures/agi-foundations/ch1</guid>
    <description><![CDATA[ Incompleteness theorems, Löb's theorem, the Löbian obstacle, refutation of Penrose ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
  </item><item>
    <title>Chapter 2 · AIXI and universal intelligence</title>
    <link>https://iohanngrig.github.io/lectures/agi-foundations/ch2</link>
    <guid>https://iohanngrig.github.io/lectures/agi-foundations/ch2</guid>
    <description><![CDATA[ Solomonoff induction, Hutter's AIXI, Legg-Hutter intelligence measure, Monte Carlo AIXI ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
  </item><item>
    <title>Chapter 3 · World models and planning-by-imagination</title>
    <link>https://iohanngrig.github.io/lectures/agi-foundations/ch3</link>
    <guid>https://iohanngrig.github.io/lectures/agi-foundations/ch3</guid>
    <description><![CDATA[ Ha-Schmidhuber, DreamerV3, JEPA, the LLM-world-model hypothesis ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
  </item><item>
    <title>Chapter 4 · Computational irreducibility and limits of optimization</title>
    <link>https://iohanngrig.github.io/lectures/agi-foundations/ch4</link>
    <guid>https://iohanngrig.github.io/lectures/agi-foundations/ch4</guid>
    <description><![CDATA[ No Free Lunch, computational irreducibility (Wolfram), PAC lower bounds, what these do not preclude ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
  </item><item>
    <title>Lectures on AGI foundations</title>
    <link>https://iohanngrig.github.io/lectures/agi-foundations/</link>
    <guid>https://iohanngrig.github.io/lectures/agi-foundations/</guid>
    <description><![CDATA[ Four chapters on the mathematical foundations of general intelligence: Gödel-Löb, AIXI, world models, and computational irreducibility. ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
  </item><item>
    <title>Chapter 1 · Potential outcomes and causal estimands</title>
    <link>https://iohanngrig.github.io/lectures/causal-inference/ch01</link>
    <guid>https://iohanngrig.github.io/lectures/causal-inference/ch01</guid>
    <description><![CDATA[ Neyman-Rubin framework, ATE/ATT/CATE, fundamental problem, Neyman variance, Fisher's randomization test ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
  </item><item>
    <title>Chapter 2 · Identification: when can data answer a causal question?</title>
    <link>https://iohanngrig.github.io/lectures/causal-inference/ch02</link>
    <guid>https://iohanngrig.github.io/lectures/causal-inference/ch02</guid>
    <description><![CDATA[ Strong ignorability, g-formula proof, Rosenbaum-Rubin propensity score theorem, sensitivity analysis ]]></description>
    <pubDate>Tue, 26 May 2026 19:00:52 GMT</pubDate>
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