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Riemannian Laplace approximations for Bayesian neural networks

Riemannian Laplace approximations for Bayesian neural networks

12 June 2023
Federico Bergamin
Pablo Moreno-Muñoz
Søren Hauberg
Georgios Arvanitidis
    BDL
ArXivPDFHTML

Papers citing "Riemannian Laplace approximations for Bayesian neural networks"

7 / 7 papers shown
Title
Reparameterization invariance in approximate Bayesian inference
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
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
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
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
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
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
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
247
9,109
0
06 Jun 2015
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