Riemannian Laplace approximations for Bayesian neural networks

12 June 2023

Papers citing "Riemannian Laplace approximations for Bayesian neural networks"

7 / 7 papers shown

Title
Reparameterization invariance in approximate Bayesian inference Hrittik Roy M. Miani Carl Henrik Ek Philipp Hennig Marvin Pfortner Lukas Tatzel Søren Hauberg BDL 42 8 0 05 Jun 2024
The Interpolating Information Criterion for Overparameterized Models Liam Hodgkinson Christopher van der Heide Roberto Salomone Fred Roosta Michael W. Mahoney 16 7 0 15 Jul 2023
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks Agustinus Kristiadi Runa Eschenhagen Philipp Hennig BDL 19 12 0 20 May 2022
Lagrangian Manifold Monte Carlo on Monge Patches M. Hartmann Mark Girolami Arto Klami 16 10 0 01 Feb 2022
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 266 0 13 Jun 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,652 0 05 Dec 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,109 0 06 Jun 2015