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HTTP/2 200 server: GitHub.com content-type: text/html; charset=utf-8 last-modified: Sun, 30 Nov 2025 05:52:54 GMT access-control-allow-origin: * etag: W/"692bdbb6-2ac9" expires: Mon, 29 Dec 2025 11:38:38 GMT cache-control: max-age=600 content-encoding: gzip x-proxy-cache: MISS x-github-request-id: 6160:328FD3:8C10DC:9D34A2:695265E6 accept-ranges: bytes age: 0 date: Mon, 29 Dec 2025 11:28:38 GMT via: 1.1 varnish x-served-by: cache-bom-vanm7210093-BOM x-cache: MISS x-cache-hits: 0 x-timer: S1767007718.199323,VS0,VE232 vary: Accept-Encoding x-fastly-request-id: 9f2c0de723eee8bd3d2e8b327882775ebd061ace content-length: 2957 Yoav Gelberg

Yoav Gelberg

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About Me

I'm a graduate student at the University of Oxford, working with Haggai Maron, Michael Bronstein and Yarin Gal. My research focuses on the symmetry and structure of neural network parameter spaces with application to deep (meta-)learning. I'm also interested in architecture reserach more broadly and in the way structure can inform learning. I spent the summer of 2025 at Sakana AI, working on positional embeddings and length generalization in LLMs.

Before Oxford, I completed my undergraduate studies at the Technion as a Rothschild scholar, studied expander graphs at the Weizmann Institute, developed fair learning algorithms at Fairgen, and taught math and programming at the ARDC.