深度学习 (Chinese Wikipedia)

Analysis of information sources in references of the Wikipedia article "深度学习" in Chinese language version.

refsWebsite

Global rank Chinese rank

23web.archive.org

1^st place

5msu.edu

1,844^th place

1,574^th place

4arxiv.org

69^th place

254^th place

4doi.org

2^nd place

23^rd place

2wired.com

193^rd place

421^st place

1microsoft.com

153^rd place

238^th place

1sanghv.com

low place

1nature.com

234^th place

227^th place

1videolectures.net

low place

1ieee.org

652^nd place

712^th place

1uni-bonn.de

6,912^th place

low place

1acm.org

1,185^th place

809^th place

1toronto.edu

low place

1nih.gov

4^th place

5^th place

1scholarpedia.org

low place

1worldcat.org

5^th place

12^th place

1nytimes.com

7^th place

31^st place

1stanford.edu

179^th place

275^th place

1lecun.com

low place

1csdn.net

low place

4,213^th place

1paddlepaddle.org

low place

1berkeleyvision.org

low place

1ronnie.ai

low place

1mxnet.io

low place

acm.org

portal.acm.org

Smolensky, P. Information processing in dynamical systems: Foundations of harmony theory. 1. 1986: 194–281. |journal=被忽略 (帮助)

arxiv.org

Bengio, Y.; Courville, A.; Vincent, P. Representation Learning: A Review and New Perspectives. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2013, 35 (8): 1798–1828. arXiv:1206.5538 .
Schmidhuber, J. Deep Learning in Neural Networks: An Overview. Neural Networks. 2015, 61: 85–117. arXiv:1404.7828 . doi:10.1016/j.neunet.2014.09.003.
Glauner, P. Deep Convolutional Neural Networks for Smile Recognition (学位论文). Imperial College London, Department of Computing. 2015. arXiv:1508.06535 .
Ng, Andrew; Dean, Jeff. Building High-level Features Using Large Scale Unsupervised Learning (PDF). 2012 [2014-09-16]. （原始内容存档 (PDF)于2017-10-12）.

berkeleyvision.org

caffe.berkeleyvision.org

Caffe （页面存档备份，存于互联网档案馆）

csdn.net

谷歌收购DNNresearch，下一个帝国呼之欲出. CSDN. 2013-03-13 [2014-07-20]. （原始内容存档于2020-03-24）.

doi.org

Schmidhuber, J. Deep Learning in Neural Networks: An Overview. Neural Networks. 2015, 61: 85–117. arXiv:1404.7828 . doi:10.1016/j.neunet.2014.09.003.
Song, H.A.; Lee, S. Y. Hierarchical Representation Using NMF. Neural Information Processing. Lectures Notes in Computer Sciences 8226. Springer Berlin Heidelberg. 2013: 466–473. ISBN 978-3-642-42053-5. doi:10.1007/978-3-642-42054-2_58.
Hinton, G. E.; Osindero, S.; Teh, Y. A fast learning algorithm for deep belief nets (PDF). Neural Computation. 2006, 18 (7): 1527–1554 [2014-09-16]. PMID 16764513. doi:10.1162/neco.2006.18.7.1527. （原始内容存档 (PDF)于2015-12-23）.
Geoffrey Hinton. Deep belief networks. Scholarpedia. 2009-05-31, 4 (5) [2018-04-02]. ISSN 1941-6016. doi:10.4249/scholarpedia.5947. （原始内容存档于2015-12-04）（英语）.

ieee.org

spectrum.ieee.org

Gomes, L. Machine-Learning Maestro Michael Jordan on the Delusions of Big Data and Other Huge Engineering Efforts. IEEE Spectrum. 20 October 2014 [2015-10-31]. （原始内容存档于2019-12-12）.

lecun.com

yann.lecun.com

http://yann.lecun.com/exdb/mnist/ （页面存档备份，存于互联网档案馆）.

microsoft.com

research.microsoft.com

Deng, L.; Yu, D. Deep Learning: Methods and Applications (PDF). Foundations and Trends in Signal Processing. 2014, 7: 3–4 [2015-10-23]. （原始内容存档 (PDF)于2016-03-14）.

msu.edu

cse.msu.edu

J. Weng, N. Ahuja and T. S. Huang, "Cresceptron: a self-organizing neural network which grows adaptively （页面存档备份，存于互联网档案馆）," Proc. International Joint Conference on Neural Networks, Baltimore, Maryland, vol I, pp. 576-581, June, 1992.
J. Weng, N. Ahuja and T. S. Huang, "Learning recognition and segmentation of 3-D objects from 2-D images （页面存档备份，存于互联网档案馆）," Proc. 4th International Conf. Computer Vision, Berlin, Germany, pp. 121-128, May, 1993.
J. Weng, N. Ahuja and T. S. Huang, "Learning recognition and segmentation using the Cresceptron （页面存档备份，存于互联网档案馆）," International Journal of Computer Vision, vol. 25, no. 2, pp. 105-139, Nov. 1997.
J. Weng, J. McClelland, A. Pentland, O. Sporns, I. Stockman, M. Sur and E. Thelen, "Autonomous Mental Development by Robots and Animals （页面存档备份，存于互联网档案馆）," Science, vol. 291, no. 5504, pp. 599 - 600, Jan. 26, 2001.
J. Weng, "Brains as Naturally Emerging Turing Machines （页面存档备份，存于互联网档案馆）," in Proc. International Joint Conference on Neural Networks, Killarney, Ireland, 8 pages, July 12-17. 2015.

mxnet.io

Mxnet. [2017-03-17]. （原始内容存档于2017-08-18）.

nature.com

Bengio, Yoshua; LeCun, Yann; Hinton, Geoffrey. Deep Learning. Nature. 2015, 521: 436–444.

nih.gov

ncbi.nlm.nih.gov

Hinton, G. E.; Osindero, S.; Teh, Y. A fast learning algorithm for deep belief nets (PDF). Neural Computation. 2006, 18 (7): 1527–1554 [2014-09-16]. PMID 16764513. doi:10.1162/neco.2006.18.7.1527. （原始内容存档 (PDF)于2015-12-23）.

nytimes.com

John Markoff. How Many Computers to Identify a Cat? 16,000.. New York Times. 25 June 2012 [2014-09-16]. （原始内容存档于2018-07-11）.

paddlepaddle.org

PaddlePaddle. [2017-07-21]. （原始内容存档于2020-12-08）.

ronnie.ai

roNNie. [2018-05-02]. （原始内容存档于2020-11-28）.

sanghv.com

Bengio, Yoshua. Learning Deep Architectures for AI (PDF). Foundations and Trends in Machine Learning. 2009, 2 (1): 1–127. （原始内容 (PDF)存档于2016-03-04）.

scholarpedia.org

Geoffrey Hinton. Deep belief networks. Scholarpedia. 2009-05-31, 4 (5) [2018-04-02]. ISSN 1941-6016. doi:10.4249/scholarpedia.5947. （原始内容存档于2015-12-04）（英语）.

stanford.edu

ufldl.stanford.edu

Convolutional Neural Network. [2014-09-16]. （原始内容存档于2020-10-29）.

toronto.edu

cs.toronto.edu

Hinton, G. E.; Osindero, S.; Teh, Y. A fast learning algorithm for deep belief nets (PDF). Neural Computation. 2006, 18 (7): 1527–1554 [2014-09-16]. PMID 16764513. doi:10.1162/neco.2006.18.7.1527. （原始内容存档 (PDF)于2015-12-23）.

uni-bonn.de

ais.uni-bonn.de

Sven Behnke. Hierarchical Neural Networks for Image Interpretation. (PDF). Lecture Notes in Computer Science 2766. Springer. 2003 [2014-09-16]. （原始内容存档 (PDF)于2021-03-08）.

videolectures.net

Collobert, R. Deep Learning for Efficient Discriminative Parsing. VideoLectures.net. April 2011. 事件发生在 7min 45s [2015-10-31]. （原始内容存档于2020-10-19）.

web.archive.org

Deng, L.; Yu, D. Deep Learning: Methods and Applications (PDF). Foundations and Trends in Signal Processing. 2014, 7: 3–4 [2015-10-23]. （原始内容存档 (PDF)于2016-03-14）.
Bengio, Yoshua. Learning Deep Architectures for AI (PDF). Foundations and Trends in Machine Learning. 2009, 2 (1): 1–127. （原始内容 (PDF)存档于2016-03-04）.
Collobert, R. Deep Learning for Efficient Discriminative Parsing. VideoLectures.net. April 2011. 事件发生在 7min 45s [2015-10-31]. （原始内容存档于2020-10-19）.
Gomes, L. Machine-Learning Maestro Michael Jordan on the Delusions of Big Data and Other Huge Engineering Efforts. IEEE Spectrum. 20 October 2014 [2015-10-31]. （原始内容存档于2019-12-12）.
J. Weng, N. Ahuja and T. S. Huang, "Cresceptron: a self-organizing neural network which grows adaptively （页面存档备份，存于互联网档案馆）," Proc. International Joint Conference on Neural Networks, Baltimore, Maryland, vol I, pp. 576-581, June, 1992.
J. Weng, N. Ahuja and T. S. Huang, "Learning recognition and segmentation of 3-D objects from 2-D images （页面存档备份，存于互联网档案馆）," Proc. 4th International Conf. Computer Vision, Berlin, Germany, pp. 121-128, May, 1993.
J. Weng, N. Ahuja and T. S. Huang, "Learning recognition and segmentation using the Cresceptron （页面存档备份，存于互联网档案馆）," International Journal of Computer Vision, vol. 25, no. 2, pp. 105-139, Nov. 1997.
J. Weng, J. McClelland, A. Pentland, O. Sporns, I. Stockman, M. Sur and E. Thelen, "Autonomous Mental Development by Robots and Animals （页面存档备份，存于互联网档案馆）," Science, vol. 291, no. 5504, pp. 599 - 600, Jan. 26, 2001.
J. Weng, "Brains as Naturally Emerging Turing Machines （页面存档备份，存于互联网档案馆）," in Proc. International Joint Conference on Neural Networks, Killarney, Ireland, 8 pages, July 12-17. 2015.
Sven Behnke. Hierarchical Neural Networks for Image Interpretation. (PDF). Lecture Notes in Computer Science 2766. Springer. 2003 [2014-09-16]. （原始内容存档 (PDF)于2021-03-08）.
Hinton, G. E.; Osindero, S.; Teh, Y. A fast learning algorithm for deep belief nets (PDF). Neural Computation. 2006, 18 (7): 1527–1554 [2014-09-16]. PMID 16764513. doi:10.1162/neco.2006.18.7.1527. （原始内容存档 (PDF)于2015-12-23）.
Geoffrey Hinton. Deep belief networks. Scholarpedia. 2009-05-31, 4 (5) [2018-04-02]. ISSN 1941-6016. doi:10.4249/scholarpedia.5947. （原始内容存档于2015-12-04）（英语）.
John Markoff. How Many Computers to Identify a Cat? 16,000.. New York Times. 25 June 2012 [2014-09-16]. （原始内容存档于2018-07-11）.
Ng, Andrew; Dean, Jeff. Building High-level Features Using Large Scale Unsupervised Learning (PDF). 2012 [2014-09-16]. （原始内容存档 (PDF)于2017-10-12）.
Convolutional Neural Network. [2014-09-16]. （原始内容存档于2020-10-29）.
http://yann.lecun.com/exdb/mnist/ （页面存档备份，存于互联网档案馆）.
D. Hernandez., "The Man Behind the Google Brain: Andrew Ng and the Quest for the New AI （页面存档备份，存于互联网档案馆）," Wired, 10 May 2013.
C. Metz., "Facebook's 'Deep Learning' Guru Reveals the Future of AI （页面存档备份，存于互联网档案馆）," Wired, 12 December 2013.
谷歌收购DNNresearch，下一个帝国呼之欲出. CSDN. 2013-03-13 [2014-07-20]. （原始内容存档于2020-03-24）.
PaddlePaddle. [2017-07-21]. （原始内容存档于2020-12-08）.
Caffe （页面存档备份，存于互联网档案馆）
roNNie. [2018-05-02]. （原始内容存档于2020-11-28）.
Mxnet. [2017-03-17]. （原始内容存档于2017-08-18）.

wired.com

D. Hernandez., "The Man Behind the Google Brain: Andrew Ng and the Quest for the New AI （页面存档备份，存于互联网档案馆）," Wired, 10 May 2013.
C. Metz., "Facebook's 'Deep Learning' Guru Reveals the Future of AI （页面存档备份，存于互联网档案馆）," Wired, 12 December 2013.

worldcat.org

Geoffrey Hinton. Deep belief networks. Scholarpedia. 2009-05-31, 4 (5) [2018-04-02]. ISSN 1941-6016. doi:10.4249/scholarpedia.5947. （原始内容存档于2015-12-04）（英语）.