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31 - Singular Learning Theory with Daniel Murfet

AXRP - the AI X-risk Research Podcast

CHAPTER

Exploring SGLD and Singular Learning Theory

This chapter investigates Stochastic Gradient Langevin Dynamics (SGLD) and its role in Bayesian sampling within deep linear networks. It emphasizes the significance of local learning coefficients and singular fluctuations in statistical learning theory, while also highlighting the importance of interdisciplinary collaboration to further advance research in this area.

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