A Capsule-unified Framework of Deep Neural Networks for Graphical Programming
| Autor: | Li, Yujian, Shan, Chuanhui |
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| Rok vydání: | 2019 |
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| Druh dokumentu: | Working Paper |
| Popis: | Recently, the growth of deep learning has produced a large number of deep neural networks. How to describe these networks unifiedly is becoming an important issue. We first formalize neural networks in a mathematical definition, give their directed graph representations, and prove a generation theorem about the induced networks of connected directed acyclic graphs. Then, using the concept of capsule to extend neural networks, we set up a capsule-unified framework for deep learning, including a mathematical definition of capsules, an induced model for capsule networks and a universal backpropagation algorithm for training them. Finally, we discuss potential applications of the framework to graphical programming with standard graphical symbols of capsules, neurons, and connections. Comment: 20 pages; 26 figures. arXiv admin note: text overlap with arXiv:1805.03551 |
| Databáze: | arXiv |
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