Investigations of Different Classes Hybrid Deep Learning Networks and Analysis of Their Efficiency in Forecasting

Author:

Hamidov Galib,Zaychenko Yuriy

Publisher

Springer Nature Switzerland

Reference14 articles.

1. Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning Book (2016). https://www.deeplearningbook.org/

2. Hinton, G.: A Practical Guide to Training Restricted Boltzmann Machines (2010). https://www.cs.toronto.edu/~hinton/absps/guideTR.pdf

3. Gan, Z., Henao, R., Carlson, D., Carin, L.: Learning Deep Sigmoid Belief Networks with Data Augmentation (2015). https://www.researchgate.net/publication/278244188_Learning_Deep_Sigmoid_Belief_Networks_with_Data_Augmentation

4. Hinton, G.: Deep Belief Networks (2009). http://www.scholarpedia.org/article/Deep_belief_networks

5. Erhan, D., Bengio, Y., Courville A., et al.: Why Does Unsupervised Pre-training Help Deep Learning? (2010). http://www.jmlr.org/papers/volume11/erhan10a/erhan10a.pdf

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