Theoretical analysis of the advantage of deepening neural networks Y Esaki, Y Nakahara, T Matsushima 2020 19th IEEE International Conference on Machine Learning and Applications …, 2020 | 1 | 2020 |
One-Shot Domain Incremental Learning Y Esaki, S Koide, T Kutsuna arXiv preprint arXiv:2403.16707, 2024 | | 2024 |
Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex Y Esaki, A Nakamura, K Kawano, R Tokuhisa, T Kutsuna arXiv preprint arXiv:2402.13765, 2024 | | 2024 |
StyleDiff: Attribute comparison between unlabeled datasets in latent disentangled space K Kawano, T Kutsuna, R Tokuhisa, A Nakamura, Y Esaki Image and Vision Computing 138, 104808, 2023 | | 2023 |
The Ratio of the Desired Parameters of Deep Neural Networks Y Esaki, Y Nakahara, T Matsushima IEICE Transactions on Fundamentals of Electronics, Communications and …, 2022 | | 2022 |