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Laplacian Autoencoders for Learning Stochastic Representations

Laplacian Autoencoders for Learning Stochastic Representations

30 June 2022
M. Miani
Frederik Warburg
Pablo Moreno-Muñoz
Nicke Skafte Detlefsen
Søren Hauberg
    UQCV
    BDL
    SSL
ArXivPDFHTML

Papers citing "Laplacian Autoencoders for Learning Stochastic Representations"

5 / 5 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
Gradients of Functions of Large Matrices
Gradients of Functions of Large Matrices
Nicholas Krämer
Pablo Moreno-Muñoz
Hrittik Roy
Søren Hauberg
27
0
0
27 May 2024
Generalization Gap in Amortized Inference
Generalization Gap in Amortized Inference
Mingtian Zhang
Peter Hayes
David Barber
BDL
CML
DRL
33
14
0
23 May 2022
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
1