Takeru Miyato | DeepAI

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Featured Co-authors

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Shin-ichi Maeda
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∙ 11/15/2021

Contrastive Representation Learning with Trainable Augmentation Channel

In contrastive representation learning, data representation is trained s...

0 Masanori Koyama, et al. ∙

∙ 05/24/2019

Robustness to Adversarial Perturbations in Learning from Incomplete Data

What is the role of unlabeled data in an inference problem, when the pre...

0 Amir Najafi, et al. ∙

∙ 11/26/2018

Collaging on Internal Representations: An Intuitive Approach for Semantic Transfiguration

We present a novel CNN-based image editing method that allows the user t...

0 Ryohei Suzuki, et al. ∙

∙ 05/16/2018

Neural Multi-scale Image Compression

This study presents a new lossy image compression method that utilizes t...

0 Ken Nakanishi, et al. ∙

∙ 02/16/2018

Spectral Normalization for Generative Adversarial Networks

One of the challenges in the study of generative adversarial networks is...

0 Takeru Miyato, et al. ∙

∙ 02/15/2018

cGANs with Projection Discriminator

We propose a novel, projection based way to incorporate the conditional ...

0 Takeru Miyato, et al. ∙

∙ 11/20/2017

Parameter Reference Loss for Unsupervised Domain Adaptation

The success of deep learning in computer vision is mainly attributed to ...

0 Jiren Jin, et al. ∙

∙ 05/31/2017

Spectral Norm Regularization for Improving the Generalizability of Deep Learning

We investigate the generalizability of deep learning based on the sensit...

0 Yuichi Yoshida, et al. ∙

∙ 04/13/2017

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

We propose a new regularization method based on virtual adversarial loss...

0 Takeru Miyato, et al. ∙

∙ 02/28/2017

Learning Discrete Representations via Information Maximizing Self-Augmented Training

Learning discrete representations of data is a central machine learning ...

0 Weihua Hu, et al. ∙

∙ 05/25/2016

Adversarial Training Methods for Semi-Supervised Text Classification

Adversarial training provides a means of regularizing supervised learnin...

0 Takeru Miyato, et al. ∙

∙ 07/02/2015

Distributional Smoothing with Virtual Adversarial Training

We propose local distributional smoothness (LDS), a new notion of smooth...

0 Takeru Miyato, et al. ∙

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