1 citations · 1 across the 7 of their papers we have counts for
Showing 2025Show all
2 papers · 1 filter
stat.ML2025
Post-Hoc Uncertainty Quantification in Pre-Trained Neural Networks via Activation-Level Gaussian Processes
Richard Bergna, Stefan Depeweg, Sergio Calvo Ordonez +3
Uncertainty quantification in neural networks through methods such as Dropout, Bayesian neural networks and Laplace approximations is either prone to underfitting or computationall…
cs.LG2025
A Gaussian Process View on Observation Noise and Initialization in Wide Neural Networks
Sergio Calvo-Ordoñez, Jonathan Plenk, Richard Bergna +4
Performing gradient descent in a wide neural network is equivalent to computing the posterior mean of a Gaussian Process with the Neural Tangent Kernel (NTK-GP), for a specific pri…