Takeru Miyato

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 27

Top Topics

Norm Regularization

Lossy Image Compression

Internal Representations

Supervised Learning

Top Venues

Publications

Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato
Neural Fourier Transform: A General Approach to Equivariant Representation Learning. ICLR (2024)
Takeru Miyato, Bernhard Jaeger, Max Welling, Andreas Geiger
GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers. ICLR (2024)
Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato
Neural Fourier Transform: A General Approach to Equivariant Representation Learning. CoRR (2023)
Takeru Miyato, Bernhard Jaeger, Max Welling, Andreas Geiger
GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers. CoRR (2023)
Takeru Miyato, Masanori Koyama, Kenji Fukumizu
Unsupervised Learning of Equivariant Structure from Sequences. CoRR (2022)
Takeru Miyato, Masanori Koyama, Kenji Fukumizu
Unsupervised Learning of Equivariant Structure from Sequences. NeurIPS (2022)
Masanori Koyama, Takeru Miyato, Kenji Fukumizu
Invariance-adapted decomposition and Lasso-type contrastive learning. CoRR (2022)
Masanori Koyama, Kentaro Minami, Takeru Miyato, Yarin Gal
Contrastive Representation Learning with Trainable Augmentation Channel. CoRR (2021)
Amir Najafi, Shin-ichi Maeda, Masanori Koyama, Takeru Miyato
Robustness to Adversarial Perturbations in Learning from Incomplete Data. CoRR (2019)
Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Shin Ishii
Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. 41 (8) (2019)
Amir Najafi, Shin-ichi Maeda, Masanori Koyama, Takeru Miyato
Robustness to Adversarial Perturbations in Learning from Incomplete Data. NeurIPS (2019)
Ken Nakanishi, Shin-ichi Maeda, Takeru Miyato, Daisuke Okanohara
Neural Multi-scale Image Compression. CoRR (2018)
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, Yuichi Yoshida
Spectral Normalization for Generative Adversarial Networks. CoRR (2018)
Takeru Miyato, Masanori Koyama
cGANs with Projection Discriminator. ICLR (Poster) (2018)
Takeru Miyato, Masanori Koyama
cGANs with Projection Discriminator. CoRR (2018)
Ken M. Nakanishi, Shin-ichi Maeda, Takeru Miyato, Daisuke Okanohara
Neural Multi-scale Image Compression. ACCV (6) (2018)
Ryohei Suzuki, Masanori Koyama, Takeru Miyato, Taizan Yonetsuji
Collaging on Internal Representations: An Intuitive Approach for Semantic Transfiguration. CoRR (2018)
Takeru Miyato, Toshiki Kataoka, Masanori Koyama, Yuichi Yoshida
Spectral Normalization for Generative Adversarial Networks. ICLR (2018)
Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama
Learning Discrete Representations via Information Maximizing Self-Augmented Training. ICML (2017)
Takeru Miyato, Daisuke Okanohara, Shin-ichi Maeda, Masanori Koyama
Synthetic Gradient Methods with Virtual Forward-Backward Networks. ICLR (Workshop) (2017)
Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama
Learning Discrete Representations via Information Maximizing Self Augmented Training. CoRR (2017)
Yuichi Yoshida, Takeru Miyato
Spectral Norm Regularization for Improving the Generalizability of Deep Learning. CoRR (2017)
Jiren Jin, Richard G. Calland, Takeru Miyato, Brian K. Vogel, Hideki Nakayama
Parameter Reference Loss for Unsupervised Domain Adaptation. CoRR (2017)
Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Shin Ishii
Virtual Adversarial Training: a Regularization Method for Supervised and Semi-supervised Learning. CoRR (2017)
Takeru Miyato, Andrew M. Dai, Ian J. Goodfellow
Adversarial Training Methods for Semi-Supervised Text Classification. ICLR (Poster) (2017)
Takeru Miyato, Andrew M. Dai, Ian J. Goodfellow
Virtual Adversarial Training for Semi-Supervised Text Classification. CoRR (2016)
Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Ken Nakae, Shin Ishii
Distributional Smoothing by Virtual Adversarial Examples. ICLR (Poster) (2016)