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About On The Origin of Deep Learning: Haohan Wang Bhiksha Raj
This paper reviews the evolutionary history of major deep learning models from their origins in neural networks modeling the human brain in the 19th century to modern deep learning architectures like convolutional neural networks (CNNs), deep belief networks (DBNs), and recurrent neural networks (RNNs). It discusses how initial ideas were developed into early neural network models and how these preliminary models evolved over decades of research into their current forms. The paper aims to provide background on the development of these models and directions to guide future deep learning research.
Detailed Information
| Author: | ['Ding'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 72 |
| Language: | English |
| Format: | |
| Price: | FREE |
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