第十六章 典型网络结构

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教学资料

  • 教学参考
  • 课件
  • 小清爱提问:什么是卷积神经网络?[]
  • 小清爱提问:什么是循环神经网络?[]

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]
  • 机器之心:卷积神经网络 [12]
  • 机器之心:一文简述循环神经网络[13]
  • 量子位:什么是自编码器 [14]


视频展示

  • 全连接网络展示 [15]
  • 全连接层展示 [16]
  • Disclaimer CNN 展示 [17]
  • CNN_Otavio_Good 的CNN展示 [18]
  • 知多少:什么是循环神经网络[19]
  • 知多少:什么是卷积神经网络[20]

演示链接

  • Andrej Karpathy's CNN demo [21]
  • Neural Net demo [22]
  • Neural Net training demo [23]
  • Quick draw, and let NN guess [24]

开发者资源

  • Python package for neural nets: PyTorch [25] TensorFlow[26] NeuralLab[27]


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" [28]
  • 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 [29]
  • 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. [30]
  • Elman, Jeffrey L. (1990). "Finding Structure in Time". Cognitive Science. 14 (2): 179–211. [31]
  • 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. [32]
  • 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). [33]
  • 王东,机器学习导论,第三章,神经模型,2021,清华大学出版社 [34]
  • Christopher M. Bishop, Neural Networks for Pattern Recognition [35]
  • Christopher M. Bishop, Pattern Recognition and Machine Learning [36]