Media Summary: Daniel Murfet (Timaeus) Safety-Guaranteed LLMs. This seminar series is an introduction to Watanabe's This talk was given as a part of Plectics Labs Interdisciplinary Colloquium May 2024. Speaker: Jesse Hoogland Affiliation: ...

31 Singular Learning Theory With - Detailed Analysis & Overview

Daniel Murfet (Timaeus) Safety-Guaranteed LLMs. This seminar series is an introduction to Watanabe's This talk was given as a part of Plectics Labs Interdisciplinary Colloquium May 2024. Speaker: Jesse Hoogland Affiliation: ... Time and Place Thursday, June 11th, 2026, 10:30 AM, room B220 Speaker Daniel Barzilai (Weizmann) Title Some Very Old and ... SLT for interpretability takes Watanabe's "knowledge is a In the SLT seminar, Vahid Shahverdi from the KTH Royal Institute of Technology talks about his recent paper "

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31 - Singular Learning Theory with Daniel Murfet
Jesse Hoogland - Singular Learning Theory and AI Safety
In-context learning in SLT Pt 2 - Singular Learning Theory Seminar 31
38.2 - Jesse Hoogland on Singular Learning Theory
Theoretical And Empirical Aspects Of Singular Learning Theory For AI Alignment
Singular Learning Theory - Seminar 2 - Fisher information, KL-divergence and singular models
Singular Learning Theory - Seminar 1 - What is learning?
Jesse Hoogland - Singular Learning Theory: Overview And Recent Evidence
Jesse Hoogland - Singular Learning Theory
Daniel Barzilai - Some Very Old and Very New Problems in Learning Theory
Studying Model Asymptotics with Singular Learning Theory, Shaowei Lin
Singular Learning Theory: Outlook - Daniel Murfet
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31 - Singular Learning Theory with Daniel Murfet

31 - Singular Learning Theory with Daniel Murfet

What's going on with deep

Jesse Hoogland - Singular Learning Theory and AI Safety

Jesse Hoogland - Singular Learning Theory and AI Safety

Jesse Hoogland presented “

In-context learning in SLT Pt 2 - Singular Learning Theory Seminar 31

In-context learning in SLT Pt 2 - Singular Learning Theory Seminar 31

We return to the topic of in-context

38.2 - Jesse Hoogland on Singular Learning Theory

38.2 - Jesse Hoogland on Singular Learning Theory

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Theoretical And Empirical Aspects Of Singular Learning Theory For AI Alignment

Theoretical And Empirical Aspects Of Singular Learning Theory For AI Alignment

Daniel Murfet (Timaeus) https://simons.berkeley.edu/talks/daniel-murfet-timaeus-2025-04-18 Safety-Guaranteed LLMs.

Singular Learning Theory - Seminar 2 - Fisher information, KL-divergence and singular models

Singular Learning Theory - Seminar 2 - Fisher information, KL-divergence and singular models

This seminar series is an introduction to Watanabe's

Singular Learning Theory - Seminar 1 - What is learning?

Singular Learning Theory - Seminar 1 - What is learning?

This seminar series is an introduction to Watanabe's

Jesse Hoogland - Singular Learning Theory: Overview And Recent Evidence

Jesse Hoogland - Singular Learning Theory: Overview And Recent Evidence

This talk was given as a part of Plectics Labs Interdisciplinary Colloquium May 2024. Speaker: Jesse Hoogland Affiliation: ...

Jesse Hoogland - Singular Learning Theory

Jesse Hoogland - Singular Learning Theory

Singular Learning Theory

Daniel Barzilai - Some Very Old and Very New Problems in Learning Theory

Daniel Barzilai - Some Very Old and Very New Problems in Learning Theory

Time and Place Thursday, June 11th, 2026, 10:30 AM, room B220 Speaker Daniel Barzilai (Weizmann) Title Some Very Old and ...

Studying Model Asymptotics with Singular Learning Theory, Shaowei Lin

Studying Model Asymptotics with Singular Learning Theory, Shaowei Lin

Singular

Singular Learning Theory: Outlook - Daniel Murfet

Singular Learning Theory: Outlook - Daniel Murfet

SLT for interpretability takes Watanabe's "knowledge is a

Learning on a Razor’s Edge: The Singularity Bias of Polynomial Neural Networks | SLT Seminar

Learning on a Razor’s Edge: The Singularity Bias of Polynomial Neural Networks | SLT Seminar

In the SLT seminar, Vahid Shahverdi from the KTH Royal Institute of Technology talks about his recent paper "