
31 - Singular Learning Theory with Daniel Murfet
AXRP - the AI X-risk Research Podcast
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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