“第十六章 典型网络结构”版本间的差异
来自cslt Wiki
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* AI100问：什么是循环神经网络？[http://aigraph.cslt.org/ai100/AI-100-107-什么是循环神经网络.pdf] | * AI100问：什么是循环神经网络？[http://aigraph.cslt.org/ai100/AI-100-107-什么是循环神经网络.pdf] | ||
* AI100问：什么是自编码器？[http://aigraph.cslt.org/ai100/AI-100-117-什么是自编码器.pdf] | * AI100问：什么是自编码器？[http://aigraph.cslt.org/ai100/AI-100-117-什么是自编码器.pdf] | ||
| − | + | * 维基百科：多层感知器[http://aigraph.cslt.org/courses/16/多层感知器.pdf][http://aigraph.cslt.org/courses/16/Multilayer_perceptron.pdf] | |
| + | * 维基百科：卷积神经网络[http://aigraph.cslt.org/courses/16/卷积神经网络.pdf][http://aigraph.cslt.org/courses/16/Convolutional_neural_network.pdf] | ||
| + | * 维基百科：循环神经网络[http://aigraph.cslt.org/courses/16/循环神经网络.pdf][http://aigraph.cslt.org/courses/16/Recurrent_neural_network.pdf] | ||
| + | * 维基百科：自编码器[http://aigraph.cslt.org/courses/16/自编码器.pdf][http://aigraph.cslt.org/courses/16/Autoencoder.pdf] | ||
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* Elman, Jeffrey L. (1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. [https://doi.org/10.1016%2F0364-0213%2890%2990002-E] | * Elman, Jeffrey L. (1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. [https://doi.org/10.1016%2F0364-0213%2890%2990002-E] | ||
* Jordan, Michael I. (1997-01-01). "Serial Order: A Parallel Distributed Processing Approach". Neural-Network Models of Cognition - Biobehavioral Foundations. Advances in Psychology. Neural-Network Models of Cognition. Vol. 121. pp. 471–495. [https://doi.org/10.1016%2Fs0166-4115%2897%2980111-2] | * Jordan, Michael I. (1997-01-01). "Serial Order: A Parallel Distributed Processing Approach". Neural-Network Models of Cognition - Biobehavioral Foundations. Advances in Psychology. Neural-Network Models of Cognition. Vol. 121. pp. 471–495. [https://doi.org/10.1016%2Fs0166-4115%2897%2980111-2] | ||
| + | * Hinton, G. E., & Zemel, R. S. (1994). Autoencoders, minimum description length and Helmholtz free energy. In Advances in neural information processing systems 6 (pp. 3-10). [https://proceedings.neurips.cc/paper/1993/file/9e3cfc48eccf81a0d57663e129aef3cb-Paper.pdf] | ||
* 王东，机器学习导论,第三章，神经模型，2021,清华大学出版社 [http://mlbook.cslt.org] | * 王东，机器学习导论,第三章，神经模型，2021,清华大学出版社 [http://mlbook.cslt.org] | ||
* Christopher M. Bishop, Neural Networks for Pattern Recognition [https://www.amazon.com/Networks-Recognition-Advanced-Econometrics-Paperback/dp/0198538642] | * Christopher M. Bishop, Neural Networks for Pattern Recognition [https://www.amazon.com/Networks-Recognition-Advanced-Econometrics-Paperback/dp/0198538642] | ||
* Christopher M. Bishop, Pattern Recognition and Machine Learning [https://www.amazon.com/-/es/Christopher-M-Bishop/dp/0387310738/ref=d_pd_sbs_sccl_3_3/143-3751675-4420139?pd_rd_w=2LB2s&content-id=amzn1.sym.3676f086-9496-4fd7-8490-77cf7f43f846&pf_rd_p=3676f086-9496-4fd7-8490-77cf7f43f846&pf_rd_r=XM3AJDN6MSM89CR1ZFV7&pd_rd_wg=QjVJC&pd_rd_r=10293f3a-8b44-4f6d-b6ee-9595387e2f18&pd_rd_i=0387310738&psc=1] | * Christopher M. Bishop, Pattern Recognition and Machine Learning [https://www.amazon.com/-/es/Christopher-M-Bishop/dp/0387310738/ref=d_pd_sbs_sccl_3_3/143-3751675-4420139?pd_rd_w=2LB2s&content-id=amzn1.sym.3676f086-9496-4fd7-8490-77cf7f43f846&pf_rd_p=3676f086-9496-4fd7-8490-77cf7f43f846&pf_rd_r=XM3AJDN6MSM89CR1ZFV7&pd_rd_wg=QjVJC&pd_rd_r=10293f3a-8b44-4f6d-b6ee-9595387e2f18&pd_rd_i=0387310738&psc=1] | ||
2022年8月5日 (五) 04:29的版本
教学资料
扩展阅读
- AI100问：什么是卷积神经网络？[1]
- AI100问：什么是循环神经网络？[2]
- AI100问：什么是自编码器？[3]
- 维基百科：多层感知器[4][5]
- 维基百科：卷积神经网络[6][7]
- 维基百科：循环神经网络[8][9]
- 维基百科：自编码器[10][11]
视频展示
演示链接
- Andrej Karpathy's CNN demo [16]
- Neural Net demo [17]
- Neural Net training demo [18]
- Quick draw, and let NN guess [19]
开发者资源
高级读者
- Fukushima, Kunihiko (1980). "Neocognitron: A Self-organizing Neural Network Model for a Mechanism of Pattern Recognition Unaffected by Shift in Position" [23]
- Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, L. D. Jackel, Backpropagation Applied to Handwritten Zip Code Recognition; AT&T Bell Laboratories [24]
- Hopfield, J. J. (1982). "Neural networks and physical systems with emergent collective computational abilities". Proceedings of the National Academy of Sciences. 79 (8): 2554–2558. [25]
- Elman, Jeffrey L. (1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. [26]
- Jordan, Michael I. (1997-01-01). "Serial Order: A Parallel Distributed Processing Approach". Neural-Network Models of Cognition - Biobehavioral Foundations. Advances in Psychology. Neural-Network Models of Cognition. Vol. 121. pp. 471–495. [27]
- Hinton, G. E., & Zemel, R. S. (1994). Autoencoders, minimum description length and Helmholtz free energy. In Advances in neural information processing systems 6 (pp. 3-10). [28]
- 王东，机器学习导论,第三章，神经模型，2021,清华大学出版社 [29]
- Christopher M. Bishop, Neural Networks for Pattern Recognition [30]
- Christopher M. Bishop, Pattern Recognition and Machine Learning [31]
