Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel

30 September 2022

Papers citing "Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel"

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 39 8 0 05 Jun 2024
Stochastic Marginal Likelihood Gradients using Neural Tangent Kernels Alexander Immer Tycho F. A. van der Ouderaa Mark van der Wilk Gunnar Rätsch Bernhard Schölkopf BDL 22 11 0 06 Jun 2023
The Geometry of Neural Nets' Parameter Spaces Under Reparametrization Agustinus Kristiadi Felix Dangel Philipp Hennig 11 10 0 14 Feb 2023
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization Stanislaw Jastrzebski Devansh Arpit Oliver Åstrand Giancarlo Kerg Huan Wang Caiming Xiong R. Socher Kyunghyun Cho Krzysztof J. Geras AI4CE 177 65 0 28 Dec 2020
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 268 5,652 0 05 Dec 2016
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,878 0 15 Sep 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