Masanori Koyama

According to our database, Masanori Koyama authored at least 31 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Extended Flow Matching: a Method of Conditional Generation with Generalized Continuity Equation.

Noboru Isobe, Masanori Koyama, Kohei Hayashi, Kenji Fukumizu

CoRR, 2024

2023

Neural Fourier Transform: A General Approach to Equivariant Representation Learning.

Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato

CoRR, 2023

2022

Invariance-adapted decomposition and Lasso-type contrastive learning.

Masanori Koyama, Takeru Miyato, Kenji Fukumizu

CoRR, 2022

Unsupervised Learning of Equivariant Structure from Sequences.

Takeru Miyato, Masanori Koyama, Kenji Fukumizu

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.

Masanori Koyama, Kentaro Minami, Takeru Miyato, Yarin Gal

CoRR, 2021

Reconnaissance for Reinforcement Learning with Safety Constraints.

Shin-ichi Maeda, Hayato Watahiki, Yi Ouyang, Shintarou Okada, Masanori Koyama, Prabhat Nagarajan

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2021

2020

Train Sparsely, Generate Densely: Memory-Efficient Unsupervised Training of High-Resolution Temporal GAN.

Masaki Saito, Shunta Saito, Masanori Koyama, Sosuke Kobayashi

Int. J. Comput. Vis., 2020

Out-of-Distribution Generalization with Maximal Invariant Predictor.

Masanori Koyama, Shoichiro Yamaguchi

CoRR, 2020

Learning Structured Latent Factors from Dependent Data: A Generative Model Framework from Information-Theoretic Perspective.

Ruixiang Zhang, Masanori Koyama, Katsuhiko Ishiguro

CoRR, 2020

Meta Learning as Bayes Risk Minimization.

Shin-ichi Maeda, Toshiki Nakanishi, Masanori Koyama

CoRR, 2020

Online-Codistillation Meets LARS, Going beyond the Limit of Data Parallelism in Deep Learning.

Shogo Murai, Hiroaki Mikami, Masanori Koyama, Shuji Suzuki, Takuya Akiba

Proceedings of the Fourth IEEE/ACM Workshop on Deep Learning on Supercomputers, 2020

Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective.

Ruixiang Zhang, Masanori Koyama, Katsuhiko Ishiguro

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

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

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

IEEE Trans. Pattern Anal. Mach. Intell., 2019

Reconnaissance and Planning algorithm for constrained MDP.

Shin-ichi Maeda, Hayato Watahiki, Shintarou Okada, Masanori Koyama

CoRR, 2019

A Differentiable Gaussian-like Distribution on Hyperbolic Space for Gradient-Based Learning.

Yoshihiro Nagano, Shoichiro Yamaguchi, Yasuhiro Fujita, Masanori Koyama

CoRR, 2019

Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks.

Katsuhiko Ishiguro, Shin-ichi Maeda, Masanori Koyama

CoRR, 2019

Robustness to Adversarial Perturbations in Learning from Incomplete Data.

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

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation.

Mitsuru Kusumoto, Takuya Inoue, Gentaro Watanabe, Takuya Akiba, Masanori Koyama

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Optuna: A Next-generation Hyperparameter Optimization Framework.

Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning.

Yoshihiro Nagano, Shoichiro Yamaguchi, Yasuhiro Fujita, Masanori Koyama

Proceedings of the 36th International Conference on Machine Learning, 2019

Distributional Concavity Regularization for GANs.

Shoichiro Yamaguchi, Masanori Koyama

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

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

Ryohei Suzuki, Masanori Koyama, Takeru Miyato, Taizan Yonetsuji

CoRR, 2018

Spectral Normalization for Generative Adversarial Networks.

Takeru Miyato, Toshiki Kataoka, Masanori Koyama, Yuichi Yoshida

Proceedings of the 6th International Conference on Learning Representations, 2018

cGANs with Projection Discriminator.

Takeru Miyato, Masanori Koyama

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Synthetic Gradient Methods with Virtual Forward-Backward Networks.

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

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Distributional Smoothing by Virtual Adversarial Examples.

Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Ken Nakae, Shin Ishii

Proceedings of the 4th International Conference on Learning Representations, 2016

2015

Efficient Monte Carlo Image Analysis for the Location of Vascular Entity.

Henrik Skibbe, Marco Reisert, Shin-ichi Maeda, Masanori Koyama, Shigeyuki Oba, Kei Ito, Shin Ishii

IEEE Trans. Medical Imaging, 2015

Deep learning of fMRI big data: a novel approach to subject-transfer decoding.

Sotetsu Koyamada, Yumi Shikauchi, Ken Nakae, Masanori Koyama, Shin Ishii

CoRR, 2015

Principal Sensitivity Analysis.

Sotetsu Koyamada, Masanori Koyama, Ken Nakae, Shin Ishii

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2015

2014

A Statistical Method of Identifying Interactions in Neuron-Glia Systems Based on Functional Multicell Ca2+ Imaging.

Ken Nakae, Yuji Ikegaya, Tomoe Ishikawa, Shigeyuki Oba, Hidetoshi Urakubo, Masanori Koyama, Shin Ishii

PLoS Comput. Biol., 2014

2012

Weak Error Analysis of Numerical Methods for Stochastic Models of Population Processes.

David F. Anderson, Masanori Koyama

Multiscale Model. Simul., 2012