24 citations · 71 across the 22 of their papers we have counts for
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cs.LG2023
On the curvature of the loss landscape
Alison Pouplin, Hrittik Roy, Sidak Pal Singh +1
One of the main challenges in modern deep learning is to understand why such over-parameterized models perform so well when trained on finite data. A way to analyze this generaliza…
stat.ML2023
Riemannian Laplace approximations for Bayesian neural networks
Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg +1
Bayesian neural networks often approximate the weight-posterior with a Gaussian distribution. However, practical posteriors are often, even locally, highly non-Gaussian, and empiri…