Publications

Neural Fourier Transform: A General Approach to Equivariant Representation Learning

ICLR 2024

By : Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato

Neural Fourier Transform: A General Approach to Equivariant Representation Learning

ICLR 2024

Machine Learning / Deep Learning

By : Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato

Unsupervised Learning of Equivariant Structure from Sequence

NeurIPS 2022

Machine Learning / Deep Learning

By : Takeru Miyato, Masanori Koyama, Kenji Fukumizu

Robustness to Adversarial Perturbations in Learning from Incomplete Data

NeurIPS 2019

Machine Learning / Deep Learning

By : Amir Najafi, Shin-ichi Maeda, Masanori Koyama, Takeru Miyato

Spectral Normalization for Generative Adversarial Networks

ICLR 2018

Machine Learning / Deep Learning

By : Takeru Miyato, Toshiki Kataoka, Masanori Koyama, Yuichi Yoshida

cGANs with Projection Discriminator

ICLR 2018

Machine Learning / Deep Learning

By : Takeru Miyato, Masanori Koyama

Synthetic Gradient Methods with Virtual Forward-Backward Networks

ICLR2017 Workshop

Machine Learning / Deep Learning

By : Takeru Miyato, Daisuke Okanohara, Shin-ichi Maeda, Masanori Koyama

Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning

IEEE TPAMI

Machine Learning / Deep Learning

By : Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Shin Ishii

Learning Discrete Representations via Information Maximizing Self-Augmented Training

ICML 2017

Machine Learning / Deep Learning

By : Weihua Hu, Takeru Miyato, Seiya Tokui, Eiichi Matsumoto, Masashi Sugiyama