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Picture for Seiya Tokui

Chainer: A Deep Learning Framework for Accelerating the Research Cycle


Aug 01, 2019
Seiya Tokui, Ryosuke Okuta, Takuya Akiba, Yusuke Niitani, Toru Ogawa, Shunta Saito, Shuji Suzuki, Kota Uenishi, Brian Vogel, Hiroyuki Yamazaki Vincent

* Accepted for Applied Data Science Track in KDD'19 

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Adversarial Attacks and Defences Competition


Mar 31, 2018
Alexey Kurakin, Ian Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang, Tianyu Pang, Jun Zhu, Xiaolin Hu, Cihang Xie, Jianyu Wang, Zhishuai Zhang, Zhou Ren, Alan Yuille, Sangxia Huang, Yao Zhao, Yuzhe Zhao, Zhonglin Han, Junjiajia Long, Yerkebulan Berdibekov, Takuya Akiba, Seiya Tokui, Motoki Abe

* 36 pages, 10 figures 

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Learning Discrete Representations via Information Maximizing Self-Augmented Training


Jun 14, 2017
Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama

* To appear at ICML 2017 

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Reparameterization trick for discrete variables


Nov 04, 2016
Seiya Tokui, Issei sato


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