
31 - Singular Learning Theory with Daniel Murfet
AXRP - the AI X-risk Research Podcast
The Impact of Initialization in Deep Learning
This chapter explores the crucial role of parameter initialization in deep learning models, emphasizing how variance can affect convergence and learning dynamics. It also examines the relationship between initialization, singular learning theory, and Bayesian interpretations, shedding light on the implications for deep network performance.
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