Takeru Miyato

Orcid: 0000-0002-7363-1773

According to our database1, Takeru Miyato authored at least 19 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
GTA: A Geometry-Aware Attention Mechanism for Multi-View Transformers.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Neural Fourier Transform: A General Approach to Equivariant Representation Learning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2022
Invariance-adapted decomposition and Lasso-type contrastive learning.
CoRR, 2022

Unsupervised Learning of Equivariant Structure from Sequences.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Contrastive Representation Learning with Trainable Augmentation Channel.
CoRR, 2021

2019
Unsupervised Discrete Representation Learning.
Proceedings of the Explainable AI: Interpreting, 2019

Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2019

Robustness to Adversarial Perturbations in Learning from Incomplete Data.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

2018
Collaging on Internal Representations: An Intuitive Approach for Semantic Transfiguration.
CoRR, 2018

Spectral Normalization for Generative Adversarial Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

cGANs with Projection Discriminator.
Proceedings of the 6th International Conference on Learning Representations, 2018

Neural Multi-scale Image Compression.
Proceedings of the Computer Vision - ACCV 2018, 2018

2017
Parameter Reference Loss for Unsupervised Domain Adaptation.
CoRR, 2017

Spectral Norm Regularization for Improving the Generalizability of Deep Learning.
CoRR, 2017

Learning Discrete Representations via Information Maximizing Self-Augmented Training.
Proceedings of the 34th International Conference on Machine Learning, 2017

Synthetic Gradient Methods with Virtual Forward-Backward Networks.
Proceedings of the 5th International Conference on Learning Representations, 2017

Adversarial Training Methods for Semi-Supervised Text Classification.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Distributional Smoothing by Virtual Adversarial Examples.
Proceedings of the 4th International Conference on Learning Representations, 2016

Virtual Adversarial Training for Semi-Supervised Text Classification.
CoRR, 2016


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