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Evaluating Dropout Placements in Bayesian Regression Resnet Cover

Evaluating Dropout Placements in Bayesian Regression Resnet

Journal of Artificial Intelligence and Soft Computing Research
Volume 12 (2022): Issue 1 (January 2022)
By: Lei Shi,  Cosmin Copot and  Steve Vanlanduit  
Open Access
|Oct 2021

Authors

Lei Shi

lei.shi@uantwerpen.be

InViLab, Falcuty of Applied Engineering, University of Antwerp Groenenborgerlaan, Antwerp, Belgium

Cosmin Copot

InViLab, Falcuty of Applied Engineering, University of Antwerp Groenenborgerlaan, Antwerp, Belgium

Steve Vanlanduit

InViLab, Falcuty of Applied Engineering, University of Antwerp Groenenborgerlaan, Antwerp, Belgium
DOI: https://doi.org/10.2478/jaiscr-2022-0005
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Language: English
Page range: 61 - 73
Submitted on: Dec 4, 2020
|
Accepted on: Jul 2, 2021
|
Published on: Oct 8, 2021
Published by: SAN University
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
Regression,
Bayesian Neural Network,
MC Dropout
Related subjects:
Computer sciences,
Artificial intelligence,
Databases and data mining

© 2021 Lei Shi, Cosmin Copot, Steve Vanlanduit, published by SAN University
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

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