Seuraa
Takeru Miyato
Takeru Miyato
University of Tübingen, Preferred Networks, Inc.
Vahvistettu sähköpostiosoite verkkotunnuksessa uni-tuebingen.de - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Spectral Normalization for Generative Adversarial Networks
T Miyato, T Kataoka, M Koyama, Y Yoshida
International Conference on Learning Representations (ICLR), 2018
56562018
Virtual adversarial training: a regularization method for supervised and semi-supervised learning
T Miyato, S Maeda, K Masanori, S Ishii
IEEE transactions on pattern analysis and machine intelligence 41 (8), 1979-1993, 2018
33122018
Adversarial Training Methods for Semi-Supervised Text Classification
T Miyato, AM Dai, I Goodfellow
International Conference on Learning Representations (ICLR), 2017
14002017
cGANs with Projection Discriminator
T Miyato, M Koyama
International Conference on Learning Representations (ICLR), 2018
6702018
Distributional smoothing with virtual adversarial training
T Miyato, S Maeda, M Koyama, K Nakae, S Ishii
arXiv preprint arXiv:1507.00677, 2015
5842015
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
5782017
Spectral norm regularization for improving the generalizability of deep learning
Y Yoshida, T Miyato
arXiv preprint arXiv:1705.10941, 2017
4042017
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
1432019
Spatially controllable image synthesis with internal representation collaging
R Suzuki, M Koyama, T Miyato, T Yonetsuji, H Zhu
arXiv preprint arXiv:1811.10153, 2018
492018
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
422019
Unsupervised learning of equivariant structure from sequences
T Miyato, M Koyama, K Fukumizu
Advances in Neural Information Processing Systems 35, 768-781, 2022
142022
Gta: A geometry-aware attention mechanism for multi-view transformers
T Miyato, B Jaeger, M Welling, A Geiger
arXiv preprint arXiv:2310.10375, 2023
112023
Image generation method, image generation apparatus, and image generation program
T Miyato
US Patent 11,048,999, 2021
92021
Data discriminator training method, data discriminator training apparatus, non-transitory computer readable medium, and training method
T Miyato
US Patent 11,593,663, 2023
72023
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
52017
Neural fourier transform: A general approach to equivariant representation learning
M Koyama, K Fukumizu, K Hayashi, T Miyato
arXiv preprint arXiv:2305.18484, 2023
42023
Generative Adversarial Network (GAN)
T Miyato, M Koyama
Computer Vision: A Reference Guide, 1-6, 2020
32020
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
Contrastive representation learning with trainable augmentation channel
M Koyama, K Minami, T Miyato, Y Gal
arXiv preprint arXiv:2111.07679, 2021
22021
Invariance-adapted decomposition and lasso-type contrastive learning
M Koyama, T Miyato, K Fukumizu
arXiv preprint arXiv:2210.07413, 2022
12022
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