Comparison between Adam, AdaMax and Adam W optimizers to implement a Weather Forecast based on Neural Networks for the Andean city of Quito

The main function of an optimizer is to determine in what measure to change the weights and the learning rate of the neural network to reduce losses. One of the best known optimizers is Adam, which main advantage is the invariance of the magnitudes of the parameter updates with respect to the change...

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Bibliographic Details
Published in:	2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM) pp. 1 - 6
Main Authors:	Llugsi, Ricardo, Yacoubi, Samira El, Fontaine, Allyx, Lupera, Pablo
Format:	Conference Proceeding
Language:	English
Published:	IEEE 12.10.2021
Subjects:	Adam Adam W AdaMax Bayesian Convolutional Dropout Encoder-Decoder Neural Network Neural networks Optimizer Temperature distribution Time Series Time series analysis Uncertainty Urban areas Walk-Forward validation Weather forecasting Weight measurement
Online Access:	Get full text
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