フォロー
Masanori Yamada
Masanori Yamada
確認したメール アドレス: hco.ntt.co.jp
タイトル
引用先
引用先
Variational autoencoder with implicit optimal priors
H Takahashi, T Iwata, Y Yamanaka, M Yamada, S Yagi
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5066-5073, 2019
332019
Autoencoding binary classifiers for supervised anomaly detection
Y Yamanaka, T Iwata, H Takahashi, M Yamada, S Kanai
Pacific Rim International Conference on Artificial Intelligence, 647-659, 2019
232019
Omega-Omega interaction from 2+ 1-flavor lattice quantum chromodynamics
M Yamada, K Sasaki, S Aoki, T Hatsuda, Y Ikeda, T Inoue, N Ishii, ...
Progress of theoretical and experimental physics 2015 (7), 2015
222015
Student-t Variational Autoencoder for Robust Density Estimation.
H Takahashi, T Iwata, Y Yamanaka, M Yamada, S Yagi
IJCAI, 2696-2702, 2018
212018
SHELXS-97, Program for the Solution of Crystal Structures SHELXS-97, Program for the Solution of Crystal Structures, 1997
S Toyota, Y Okamoto, T Ishikawa, T IWANAGA, M YAMADA
Bulletin of the Chemical Society of Japan 82 (10), 1287-1291, 2009
112009
Macro action reinforcement learning with sequence disentanglement using variational autoencoder
K Heecheol, M Yamada, K Miyoshi, H Yamakawa
arXiv preprint arXiv:1903.09366, 2019
42019
Favae: Sequence disentanglement using information bottleneck principle
M Yamada, H Kim, K Miyoshi, H Yamakawa
arXiv preprint arXiv:1902.08341, 2019
42019
Disentangled representations for sequence data using information bottleneck principle
M Yamada, H Kim, K Miyoshi, T Iwata, H Yamakawa
Asian Conference on Machine Learning, 305-320, 2020
32020
Molecular structure of chlorocycloheptane in inclusion compound with 9, 9′-bianthryl and gelation during crystallization
S Toyota, Y Okamoto, T Ishikawa, T Iwanaga, M Yamada
Bulletin of the Chemical Society of Japan 82 (2), 182-186, 2009
22009
Detecting device, detecting method, and detecting program
H Takahashi, T Iwata, Y Yamanaka, M Yamada, S Yagi
US Patent App. 17/253,131, 2021
12021
Constraining Logits by Bounded Function for Adversarial Robustness
S Kanai, M Yamada, S Yamaguchi, H Takahashi, Y Ida
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
12021
Smoothness Analysis of Loss Functions of Adversarial Training
S Kanai, M Yamada, H Takahashi, Y Yamanaka, Y Ida
12021
Absum: Simple regularization method for reducing structural sensitivity of convolutional neural networks
S Kanai, Y Ida, Y Fujiwara, M Yamada, S Adachi
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4394-4403, 2020
12020
Reinforcement Learning in Latent Action Sequence Space
H Kim, M Yamada, K Miyoshi, T Iwata, H Yamakawa
2020 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2020
12020
Familial cardiomyopathy with different clinical features in individual members
K Kudo, M Yamada, H Imai, M Katagiri, S Ozawa, Y Ida, R Okada
Journal of Cardiology 17 (4), 907-914, 1987
11987
Evaluation device, evaluation method, and evaluation program
T Takahashi, M Yamada
US Patent App. 17/441,701, 2022
2022
Detection device and detection method
M Yamada, Y Igarashi, Y Yamanaka
US Patent App. 16/973,433, 2021
2021
Smoothness Analysis of Adversarial Training
S Kanai, M Yamada, H Takahashi, Y Yamanaka, Y Ida
arXiv preprint arXiv:2103.01400, 2021
2021
Adversarial Training Makes Weight Loss Landscape Sharper in Logistic Regression
M Yamada, S Kanai, T Iwata, T Takahashi, Y Yamanaka, H Takahashi, ...
arXiv preprint arXiv:2102.02950, 2021
2021
Student-t Variational Autoencoder for Robust Multivariate Density EstimationStudent-t VAE によるロバスト確率密度推定
H Takahashi, T Iwata, Y Yamanaka, M Yamada, S Yagi, H Kashima
Transactions of the Japanese Society for Artificial Intelligence 36 (3), 2021
2021
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