| Learning Koopman invariant subspaces for dynamic mode decomposition N Takeishi, Y Kawahara, T Yairi Advances in Neural Information Processing Systems 30, 1130-1140, 2017 | 470 | 2017 |
| A data-driven health monitoring method for satellite housekeeping data based on probabilistic clustering and dimensionality reduction T Yairi, N Takeishi, T Oda, Y Nakajima, N Nishimura, N Takata IEEE Transactions on Aerospace and Electronic Systems 53 (3), 1384-1401, 2017 | 196 | 2017 |
| Recent developments in aerial robotics: A survey and prototypes overview CF Liew, D DeLatte, N Takeishi, T Yairi preprint, 2017 | 104 | 2017 |
| Subspace dynamic mode decomposition for stochastic Koopman analysis N Takeishi, Y Kawahara, T Yairi Physical Review E 96, 033310, 2017 | 92 | 2017 |
| Physics-integrated variational autoencoders for robust and interpretable generative modeling N Takeishi, A Kalousis Advances in Neural Information Processing Systems 34, 14809-14821, 2021 | 84 | 2021 |
| Bayesian dynamic mode decomposition N Takeishi, Y Kawahara, Y Tabei, T Yairi Proceedings of the 26th International Joint Conference on Artificial …, 2017 | 77 | 2017 |
| Shapley values of reconstruction errors of PCA for explaining anomaly detection N Takeishi Proceedings of 2019 International Conference on Data Mining Workshops, 739-798, 2019 | 52 | 2019 |
| Anomaly detection from multivariate time-series with sparse representation N Takeishi, T Yairi Proceedings of the 2014 IEEE International Conference on Systems, Man and …, 2014 | 45 | 2014 |
| Data-driven spectral analysis for coordinative structures in periodic human locomotion K Fujii, N Takeishi, B Kibushi, M Kouzaki, Y Kawahara Scientific Reports 9, 16755, 2019 | 29 | 2019 |
| Physically-interpretable classification of biological network dynamics for complex collective motions K Fujii, N Takeishi, M Hojo, Y Inaba, Y Kawahara Scientific Reports 10, 3005, 2020 | 27 | 2020 |
| Learning dynamics models with stable invariant sets N Takeishi, Y Kawahara Proceedings of the 35th AAAI Conference on Artificial Intelligence, 9782-9790, 2021 | 23 | 2021 |
| Evaluation of interest-region detectors and descriptors for automatic landmark tracking on asteroids N Takeishi, A Tanimoto, T Yairi, Y Tsuda, F Terui, N Ogawa, Y Mimasu Transactions of the Japan Society for Aeronautical and Space Sciences 58 (1 …, 2015 | 21 | 2015 |
| Decentralized policy learning with partial observation and mechanical constraints for multi-person modeling K Fujii, N Takeishi, Y Kawahara, K Takeda Neural Networks 171, 40-52, 2024 | 20 | 2024 |
| Learning interaction rules from multi-animal trajectories via augmented behavioral models K Fujii, N Takeishi, K Tsutsui, E Fujioka, N Nishiumi, R Tanaka, ... Advances in Neural Information Processing Systems 34, 11108-11122, 2021 | 20 | 2021 |
| A characteristic function for Shapley-value-based attribution of anomaly scores N Takeishi, Y Kawahara Transactions on Machine Learning Research, 2023 | 19* | 2023 |
| Estimating counterfactual treatment outcomes over time in complex multi-vehicle simulation K Fujii, K Takeuchi, A Kuribayashi, N Takeishi, Y Kawahara, K Takeda Proceedings of the 30th ACM SIGSPATIAL International Conference on Advances …, 2022 | 19* | 2022 |
| Asteroid flyby cycler trajectory design using deep neural networks N Ozaki, K Yanagida, T Chikazawa, N Pushparaj, N Takeishi, R Hyodo Journal of Guidance, Control, and Dynamics 45 (8), 1496-1511, 2022 | 18 | 2022 |
| Dynamic and static topic model for analyzing time-series document collections R Hida, N Takeishi, T Yairi, K Hori Proceedings of the 56th Annual Meeting of the Association for Computational …, 2018 | 18 | 2018 |
| Visual localization for asteroid touchdown operation based on local image features Y Anzai, T Yairi, N Takeishi, Y Tsuda, N Ogawa Astrodynamics 4, 149-161, 2020 | 17 | 2020 |
| Sparse nonnegative dynamic mode decomposition N Takeishi, Y Kawahara, T Yairi Proceedings of the 2017 IEEE International Conference on Image Processing …, 2017 | 16 | 2017 |
Takehisa YAIRIThe University of Tokyo, Research Center for Advanced Science and Technology確認したメール アドレス: g.ecc.u-tokyo.ac.jp
