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Takeru Miyato
Takeru Miyato
University of Tübingen, Preferred Networks, Inc.
Verified email at uni-tuebingen.de - Homepage
Title
Cited by
Cited by
Year
Spectral Normalization for Generative Adversarial Networks
T Miyato, T Kataoka, M Koyama, Y Yoshida
International Conference on Learning Representations (ICLR), 2018
37202018
Virtual adversarial training: a regularization method for supervised and semi-supervised learning
T Miyato, S Maeda, S Ishii, M Koyama
IEEE transactions on pattern analysis and machine intelligence (TPAMI), 2019
20682019
Adversarial Training Methods for Semi-Supervised Text Classification
T Miyato, AM Dai, I Goodfellow
International Conference on Learning Representations (ICLR), 2017
8702017
Distributional Smoothing with Virtual Adversarial Training
T Miyato, S Maeda, M Koyama, K Nakae, S Ishii
International Conference on Learning Representations (ICLR), 2016
5002016
cGANs with Projection Discriminator
T Miyato, M Koyama
International Conference on Learning Representations (ICLR), 2018
4732018
Learning Discrete Representations via Information Maximizing Self Augmented Training
W Hu, T Miyato, S Tokui, E Matsumoto, M Sugiyama
International Conference on Machine Learning (ICML), 2017
3732017
Spectral norm regularization for improving the generalizability of deep learning
Y Yoshida, T Miyato
arXiv preprint arXiv:1705.10941, 2017
2482017
Robustness to adversarial perturbations in learning from incomplete data
A Najafi, S Maeda, M Koyama, T Miyato
Advances in Neural Information Processing Systems 32, 2019
982019
Spatially controllable image synthesis with internal representation collaging
R Suzuki, M Koyama, T Miyato, T Yonetsuji, H Zhu
arXiv preprint arXiv:1811.10153, 2018
312018
Neural multi-scale image compression
KM Nakanishi, S Maeda, T Miyato, D Okanohara
Computer Vision–ACCV 2018: 14th Asian Conference on Computer Vision, Perth …, 2019
262019
Image generation method, image generation apparatus, and image generation program
T Miyato
US Patent 11,048,999, 2021
32021
Unsupervised Discrete Representation Learning
W Hu, T Miyato, S Tokui, E Matsumoto, M Sugiyama
Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 97-119, 2019
32019
Data discriminator training method, data discriminator training apparatus, non-transitory computer readable medium, and training method
T Miyato
US Patent App. 16/726,153, 2020
22020
Invariance-adapted decomposition and Lasso-type contrastive learning
M Koyama, T Miyato, K Fukumizu
arXiv preprint arXiv:2210.07413, 2022
12022
Contrastive Representation Learning with Trainable Augmentation Channel
M Koyama, K Minami, T Miyato, Y Gal
arXiv preprint arXiv:2111.07679, 2021
12021
Synthetic Gradient Methods with Virtual Forward-Backward Networks
T Miyato, D Okanohara, S Maeda, K Masanori
Workshop on International Conference on Learning Representations (ICLR), 2017
12017
Unsupervised Learning of Equivariant Structure from Sequences
T Miyato, M Koyama, K Fukumizu
arXiv preprint arXiv:2210.05972, 2022
2022
Apparatus and method for editing data and program
R Suzuki, T Miyato, T Yonetsuji
US Patent App. 17/664,280, 2022
2022
Apparatus and method for editing data and program
R Suzuki, T Miyato, T Yonetsuji
US Patent 11,373,350, 2022
2022
Image generation method, image generation apparatus, and image generation program
T Miyato
US Patent App. 17/336,959, 2021
2021
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