Search Results for author: Motoki Abe

Found 3 papers, 2 papers with code

GraphNVP: an Invertible Flow-based Model for Generating Molecular Graphs

no code implementations25 Sep 2019 Kaushalya Madhawa, katsuhiko Ishiguro, Kosuke Nakago, Motoki Abe

In contrast, our model is the first invertible model for the whole graph components: both of dequantized node attributes and adjacency tensor are converted into latent vectors through two novel invertible flows.

Graph Generation Molecular Graph Generation +1

Adversarial Attacks and Defences Competition

1 code implementation31 Mar 2018 Alexey Kurakin, Ian Goodfellow, Samy Bengio, Yinpeng Dong, Fangzhou Liao, Ming Liang, Tianyu Pang, Jun Zhu, Xiaolin Hu, Cihang Xie, Jian-Yu 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

To accelerate research on adversarial examples and robustness of machine learning classifiers, Google Brain organized a NIPS 2017 competition that encouraged researchers to develop new methods to generate adversarial examples as well as to develop new ways to defend against them.

BIG-bench Machine Learning

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