活性化関数 (Japanese Wikipedia)

Analysis of information sources in references of the Wikipedia article "活性化関数" in Japanese language version.

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arxiv.org

Ramachandran, Prajit; Zoph, Barret; Le, Quoc V. (2017-10-27). “Searching for Activation Functions”. arXiv:1710.05941 [cs]. https://arxiv.org/abs/1710.05941.
Ziyin, Liu; Hartwig, Tilman; Ueda, Masahito (2020-10-24). “Neural Networks Fail to Learn Periodic Functions and How to Fix It”. arXiv:2006.08195 [cs, stat]. https://arxiv.org/abs/2006.08195.
Sitzmann, Vincent; Martel, Julien N. P.; Bergman, Alexander W.; Lindell, David B.; Wetzstein, Gordon (2020-06-17). “Implicit Neural Representations with Periodic Activation Functions”. arXiv:2006.09661 [cs, eess]. https://arxiv.org/abs/2006.09661.
Ian J. Goodfellow; David Warde-Farley; Mehdi Mirza; Aaron Courville; Yoshua Bengio (2013). “Maxout Networks”. 30th International Conference on Machine Learning. https://arxiv.org/abs/1302.4389.

doi.org

Yann LeCun; Yoshua Bengio; Geoffrey Hinton (2015-05-28). “Deep learning”. Nature 521 (7553): 436-444. doi:10.1038/nature14539.

dtic.mil

Broomhead, David S.; Lowe, David (1988). Radial basis functions, multi-variable functional interpolation and adaptive networks.

inria.fr

people.rennes.inria.fr

Qinghua Zhang; Albert Benveniste (1992). “Wavelet networks”. IEEE Trans. Neural Networks 3: 889-898.

jmlr.org

Xavier Glorot; Yoshua Bengio (2010). Understanding the difficulty of training deep feedforward neural networks.

lecun.com

yann.lecun.com

Yann LeCun; Leon Bottou; Genevieve B. Orr; Klaus-Robert Muller (1998). Efficient BackProp.

mit.edu

jmlr.csail.mit.edu

Xavier Glorot; Antoine Bordes; Yoshua Bengio. “Deep Sparse Rectifier Neural Networks”. Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics (AISTATS-11) 15: 315-323.

nips.cc

papers.nips.cc

Youngmin Cho; Lawrence K. Saul (2009). “Kernel Methods for Deep Learning”. Advances in Neural Information Processing Systems 22: 342-350.

stanford.edu

web.stanford.edu

Andrew L. Maas; Awni Y. Hannun; Andrew Y. Ng (2013). Rectifier Nonlinearities Improve Neural Network Acoustic Models.