Masanori Koyama

44 papers A* 9Journal 28Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Flow matching achieves almost minimax optimal convergence. ICLR Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, Masanori Koyama
2025	J	`jnl`	Inter-environmental world modeling for continuous and compositional dynamics. CoRR Kohei Hayashi, Masanori Koyama, Julian Jorge Andrade Guerreiro
2025	J	`jnl`	Simultaneous Learning of Optimal Transports for Training All-to-All Flow-Based Condition Transfer Model. CoRR Kotaro Ikeda, Masanori Koyama, Jinzhe Zhang, Kohei Hayashi, Kenji Fukumizu
2024	J	`jnl`	Extended Flow Matching: a Method of Conditional Generation with Generalized Continuity Equation. CoRR Noboru Isobe, Masanori Koyama, Kohei Hayashi, Kenji Fukumizu
2024	J	`jnl`	Flow matching achieves minimax optimal convergence. CoRR Kenji Fukumizu, Taiji Suzuki, Noboru Isobe, Kazusato Oko, Masanori Koyama
2024	A*	`conf`	Neural Fourier Transform: A General Approach to Equivariant Representation Learning. ICLR Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato
2023	J	`jnl`	Neural Fourier Transform: A General Approach to Equivariant Representation Learning. CoRR Masanori Koyama, Kenji Fukumizu, Kohei Hayashi, Takeru Miyato
2022	J	`jnl`	Invariance-adapted decomposition and Lasso-type contrastive learning. CoRR Masanori Koyama, Takeru Miyato, Kenji Fukumizu
2022	A*	`conf`	Unsupervised Learning of Equivariant Structure from Sequences. NeurIPS Takeru Miyato, Masanori Koyama, Kenji Fukumizu
2022	J	`jnl`	Unsupervised Learning of Equivariant Structure from Sequences. CoRR Takeru Miyato, Masanori Koyama, Kenji Fukumizu
2021	J	`jnl`	Contrastive Representation Learning with Trainable Augmentation Channel. CoRR Masanori Koyama, Kentaro Minami, Takeru Miyato, Yarin Gal
2021	—	`conf`	Reconnaissance for Reinforcement Learning with Safety Constraints. ECML/PKDD (2) Shin-ichi Maeda, Hayato Watahiki, Yi Ouyang, Shintarou Okada, Masanori Koyama, Prabhat Nagarajan
2020	J	`jnl`	Learning Structured Latent Factors from Dependent Data: A Generative Model Framework from Information-Theoretic Perspective. CoRR Ruixiang Zhang, Masanori Koyama, Katsuhiko Ishiguro
2020	A*	`conf`	Learning Structured Latent Factors from Dependent Data:A Generative Model Framework from Information-Theoretic Perspective. ICML Ruixiang Zhang, Masanori Koyama, Katsuhiko Ishiguro
2020	J	`jnl`	Meta Learning as Bayes Risk Minimization. CoRR Shin-ichi Maeda, Toshiki Nakanishi, Masanori Koyama
2020	—	`conf`	Online-Codistillation Meets LARS, Going beyond the Limit of Data Parallelism in Deep Learning. DLS@SC Shogo Murai, Hiroaki Mikami, Masanori Koyama, Shuji Suzuki, Takuya Akiba
2020	J	`jnl`	Out-of-Distribution Generalization with Maximal Invariant Predictor. CoRR Masanori Koyama, Shoichiro Yamaguchi
2020	J	`jnl`	Train Sparsely, Generate Densely: Memory-Efficient Unsupervised Training of High-Resolution Temporal GAN. Int. J. Comput. Vis. Masaki Saito, Shunta Saito, Masanori Koyama, Sosuke Kobayashi
2019	J	`jnl`	A Differentiable Gaussian-like Distribution on Hyperbolic Space for Gradient-Based Learning. CoRR Yoshihiro Nagano, Shoichiro Yamaguchi, Yasuhiro Fujita, Masanori Koyama
2019	A*	`conf`	A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation. NeurIPS Mitsuru Kusumoto, Takuya Inoue, Gentaro Watanabe, Takuya Akiba, Masanori Koyama
2019	J	`jnl`	A Graph Theoretic Framework of Recomputation Algorithms for Memory-Efficient Backpropagation. CoRR Mitsuru Kusumoto, Takuya Inoue, Gentaro Watanabe, Takuya Akiba, Masanori Koyama
2019	A*	`conf`	A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning. ICML Yoshihiro Nagano, Shoichiro Yamaguchi, Yasuhiro Fujita, Masanori Koyama
2019	—	`conf`	Distributional Concavity Regularization for GANs. ICLR (Poster) Shoichiro Yamaguchi, Masanori Koyama
2019	J	`jnl`	Graph Warp Module: an Auxiliary Module for Boosting the Power of Graph Neural Networks. CoRR Katsuhiko Ishiguro, Shin-ichi Maeda, Masanori Koyama
2019	A*	`conf`	Optuna: A Next-generation Hyperparameter Optimization Framework. KDD Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama
2019	J	`jnl`	Optuna: A Next-generation Hyperparameter Optimization Framework. CoRR Takuya Akiba, Shotaro Sano, Toshihiko Yanase, Takeru Ohta, Masanori Koyama
2019	J	`jnl`	Reconnaissance and Planning algorithm for constrained MDP. CoRR Shin-ichi Maeda, Hayato Watahiki, Shintarou Okada, Masanori Koyama
2019	A*	`conf`	Robustness to Adversarial Perturbations in Learning from Incomplete Data. NeurIPS Amir Najafi, Shin-ichi Maeda, Masanori Koyama, Takeru Miyato
2019	J	`jnl`	Robustness to Adversarial Perturbations in Learning from Incomplete Data. CoRR Amir Najafi, Shin-ichi Maeda, Masanori Koyama, Takeru Miyato
2019	J	`jnl`	Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Shin Ishii
2018	J	`jnl`	Collaging on Internal Representations: An Intuitive Approach for Semantic Transfiguration. CoRR Ryohei Suzuki, Masanori Koyama, Takeru Miyato, Taizan Yonetsuji
2018	—	`conf`	Spectral Normalization for Generative Adversarial Networks. ICLR Takeru Miyato, Toshiki Kataoka, Masanori Koyama, Yuichi Yoshida
2018	J	`jnl`	Spectral Normalization for Generative Adversarial Networks. CoRR Takeru Miyato, Toshiki Kataoka, Masanori Koyama, Yuichi Yoshida
2018	—	`conf`	cGANs with Projection Discriminator. ICLR (Poster) Takeru Miyato, Masanori Koyama
2018	J	`jnl`	cGANs with Projection Discriminator. CoRR Takeru Miyato, Masanori Koyama
2017	—	`conf`	Synthetic Gradient Methods with Virtual Forward-Backward Networks. ICLR (Workshop) Takeru Miyato, Daisuke Okanohara, Shin-ichi Maeda, Masanori Koyama
2017	J	`jnl`	Virtual Adversarial Training: a Regularization Method for Supervised and Semi-supervised Learning. CoRR Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Shin Ishii
2016	A*	`conf`	Distributional Smoothing by Virtual Adversarial Examples. ICLR (Poster) Takeru Miyato, Shin-ichi Maeda, Masanori Koyama, Ken Nakae, Shin Ishii
2015	J	`jnl`	Deep learning of fMRI big data: a novel approach to subject-transfer decoding. CoRR Sotetsu Koyamada, Yumi Shikauchi, Ken Nakae, Masanori Koyama, Shin Ishii
2015	J	`jnl`	Efficient Monte Carlo Image Analysis for the Location of Vascular Entity. IEEE Trans. Medical Imaging Henrik Skibbe, Marco Reisert, Shin-ichi Maeda, Masanori Koyama, Shigeyuki Oba, Kei Ito, Shin Ishii
2015	—	`conf`	Principal Sensitivity Analysis. PAKDD (1) Sotetsu Koyamada, Masanori Koyama, Ken Nakae, Shin Ishii
2014	J	`jnl`	A Statistical Method of Identifying Interactions in Neuron-Glia Systems Based on Functional Multicell Ca2+ Imaging. PLoS Comput. Biol. Ken Nakae, Yuji Ikegaya, Tomoe Ishikawa, Shigeyuki Oba, Hidetoshi Urakubo, Masanori Koyama, Shin Ishii
2014	J	`jnl`	Principal Sensitivity Analysis. CoRR Sotetsu Koyamada, Masanori Koyama, Ken Nakae, Shin Ishii
2012	J	`jnl`	Weak Error Analysis of Numerical Methods for Stochastic Models of Population Processes. Multiscale Model. Simul. David F. Anderson, Masanori Koyama