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Efficient Uncertainty Estimation in Spiking Neural Networks via
  MC-dropout

Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout

20 April 2023
Tao Sun
Bojian Yin
S. Bohté
    BDL
ArXivPDFHTML

Papers citing "Efficient Uncertainty Estimation in Spiking Neural Networks via MC-dropout"

4 / 4 papers shown
Title
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification
A Deep Bayesian Convolutional Spiking Neural Network-based CAD system with Uncertainty Quantification for Medical Images Classification
Mohaddeseh Chegini
Ali Mahloojifar
BDL
UQCV
66
0
0
23 Apr 2025
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike
  Timing Dependent Backpropagation
Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation
Nitin Rathi
G. Srinivasan
Priyadarshini Panda
Kaushik Roy
116
292
0
04 May 2020
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
5,635
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
9,042
0
06 Jun 2015
1