no code implementations • 31 Oct 2023 • Lukas Tatzel, Jonathan Wenger, Frank Schneider, Philipp Hennig
Bayesian Generalized Linear Models (GLMs) define a flexible probabilistic framework to model categorical, ordinal and continuous data, and are widely used in practice.
3 code implementations • 4 Jun 2021 • Felix Dangel, Lukas Tatzel, Philipp Hennig
Curvature in form of the Hessian or its generalized Gauss-Newton (GGN) approximation is valuable for algorithms that rely on a local model for the loss to train, compress, or explain deep networks.
