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Scalable Bayesian Inference in the Era of Deep Learning: From Gaussian Processes to Deep Neural Networks

Antoran, JavierUniversity of Cambridge2024

… more scalable. In particular, we leverage the linearised Laplace approximation to equip pre-trained neural networks with the uncertainty estimates provided by their tangent linear models. This turns the problem of Bayesian inference in neural networks into one of Bayesian inference in conjugate …

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