2023年最新的深度学习论文阅读路线图

1、第 PAGE4 页 共 NUMPAGES4 页2023年最新的深度学习论文阅读路线图深度学习论文阅读路线图 想要入门深度学习的人来说都会遇到一个共同的问题，就是应该从哪学起 这里整理了一份深度学习论文阅读路线图。 路线图按照以下四种原则制定： 从整体到局部 从过去到最前沿 从通用到特定领域 关注最新的研究成果 (由于篇幅限制，下面放出部分论文表单，完整表单请点击阅读原文查看) 有许多论文很新但值得一读。 1 深度学习的发展史和基本理论 1.0 书籍 0 Bengio, Yoshua, Ian J. Goodfellow, and Aaron Courville. Deep learning.

2、An MIT Press book. (2023). pdf (相当深度学习中的圣经，你可以在阅读论文的同时翻阅这本书) 1.1 综述 1 LeCun, Yann, Yoshua Bengio, and Geoffrey Hinton. Deep learning. Nature 521.7553 (2023): 436-444. pdf (深度学习的三巨头撰写的) 1.2 Deep Belief Network(DBN)(深度学习前夜的里程碑) 2 Hinton, Geoffrey E., Simon Osindero, and Yee-Whye Teh. A fast learning a

3、lgorithm for deep belief nets. Neural computation 18.7 (2023): 1527-1554. pdf(深度学习前身) 3 Hinton, Geoffrey E., and Ruslan R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science 313.5786 (2023): 504-507. pdf (划时代的研究) 1.3 ImageNet的进化(深度学习的萌芽) 4 Krizhevsky, Alex, Ilya Sutskev

4、er, and Geoffrey E. Hinton. Imagenet classification with deep convolutional neural networks. Advances in neural information processing systems. 2023.pdf (AlexNet, 深度学习的重大突破) 5 Simonyan, Karen, and Andrew Zisserman. Very deep convolutional networks for large-scale image recognition. arXiv preprint ar

5、Xiv:1409.1556 (2023). pdf (VGGNet,神经网络增加深度) 6 Szegedy, Christian, et al. Going deeper with convolutions. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2023. pdf (GoogLeNet) 7 He, Kaiming, et al. Deep residual learning for image recognition. arXiv preprint arXiv:1512.

6、03385 (2023). pdf(ResNet, CVPR 最好的论文) 1.4 语音识别的进化 8 Hinton, Geoffrey, et al. Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups. IEEE Signal Processing Magazine 29.6 (2023): 82-97.pdf (语言识别的重大突破) 9 Graves, Alex, Abdel-rahman Mohamed, and Geoffr

7、ey Hinton. Speech recognition with deep recurrent neural networks. 2023 IEEE international conference on acoustics, speech and signal processing. IEEE, 2023. pdf (RNN) 10 Graves, Alex, and Navdeep Jaitly. Towards End-To-End Speech Recognition with Recurrent Neural Networks. ICML. Vol. 14. 2023. pdf

8、11 Sak, Haim, et al. Fast and accurate recurrent neural network acoustic models for speech recognition. arXiv preprint arXiv:1507.06947 (2023). pdf (谷歌的语音识别系统) 12 Amodei, Dario, et al. Deep speech 2: End-to-end speech recognition in english and mandarin. arXiv preprint arXiv:1512.02595 (2023). pdf (百度的语音识别系统) 13 W. Xiong, J. Droppo, X. Huang, F. Seide, M. Seltzer, A. Stolcke, D. Yu, G. Zweig Achieving Human Parity in Conversational Speech Recognition. arXiv preprint arXiv:1610.05256 (2023).pdf (微软语音识别技术的杰出研究成果)