| Anomaly detection using autoencoders with nonlinear dimensionality reduction M Sakurada, T Yairi Proceedings of the MLSDA 2014 2nd workshop on machine learning for sensory …, 2014 | 1287 | 2014 |
| A review on the application of deep learning in system health management S Khan, T Yairi Mechanical Systems and Signal Processing 107, 241-265, 2018 | 1047 | 2018 |
| Coupled nonnegative matrix factorization unmixing for hyperspectral and multispectral data fusion N Yokoya, T Yairi, A Iwasaki IEEE Transactions on Geoscience and Remote Sensing 50 (2), 528-537, 2011 | 971 | 2011 |
| Learning Koopman invariant subspaces for dynamic mode decomposition N Takeishi, Y Kawahara, T Yairi Advances in neural information processing systems 30, 2017 | 399 | 2017 |
| An approach to spacecraft anomaly detection problem using kernel feature space R Fujimaki, T Yairi, K Machida Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005 | 358 | 2005 |
| Change-point detection in time-series data based on subspace identification Y Kawahara, T Yairi, K Machida Seventh IEEE International Conference on Data Mining (ICDM 2007), 559-564, 2007 | 162 | 2007 |
| Fault detection by mining association rules from house-keeping data T Yairi, Y Kato, K Hori proceedings of the 6th International Symposium on Artificial Intelligence …, 2001 | 154 | 2001 |
| 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 | 149 | 2017 |
| Telemetry-mining: a machine learning approach to anomaly detection and fault diagnosis for space systems T Yairi, Y Kawahara, R Fujimaki, Y Sato, K Machida 2nd IEEE International Conference on Space Mission Challenges for …, 2006 | 106 | 2006 |
| Recent developments in aerial robotics: A survey and prototypes overview CF Liew, D DeLatte, N Takeishi, T Yairi arXiv preprint arXiv:1711.10085, 2017 | 88 | 2017 |
| Structured denoising autoencoder for fault detection and analysis T Tagawa, Y Tadokoro, T Yairi Asian conference on machine learning, 96-111, 2015 | 85 | 2015 |
| Subspace dynamic mode decomposition for stochastic Koopman analysis N Takeishi, Y Kawahara, T Yairi Physical Review E 96 (3), 033310, 2017 | 81 | 2017 |
| Bayesian dynamic mode decomposition. N Takeishi, Y Kawahara, Y Tabei, T Yairi IJCAI, 2814-2821, 2017 | 72 | 2017 |
| An anomaly detection method for spacecraft using relevance vector learning R Fujimaki, T Yairi, K Machida Pacific-Asia Conference on Knowledge Discovery and Data Mining, 785-790, 2005 | 63 | 2005 |
| Unsupervised anomaly detection in unmanned aerial vehicles S Khan, CF Liew, T Yairi, R McWilliam Applied Soft Computing 83, 105650, 2019 | 58 | 2019 |
| Automated crater detection algorithms from a machine learning perspective in the convolutional neural network era DM DeLatte, ST Crites, N Guttenberg, T Yairi Advances in Space Research 64 (8), 1615-1628, 2019 | 57 | 2019 |
| Facial expression recognition and analysis: a comparison study of feature descriptors CF Liew, T Yairi IPSJ transactions on computer vision and applications 7, 104-120, 2015 | 51 | 2015 |
| Segmentation convolutional neural networks for automatic crater detection on mars DM DeLatte, ST Crites, N Guttenberg, EJ Tasker, T Yairi IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2019 | 46 | 2019 |
| Hyperspectral, multispectral, and panchromatic data fusion based on coupled non-negative matrix factorization N Yokoya, T Yairi, A Iwasaki 2011 3rd workshop on hyperspectral image and signal processing: Evolution in …, 2011 | 45 | 2011 |
| Anomaly detection from multivariate time-series with sparse representation N Takeishi, T Yairi 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC …, 2014 | 42 | 2014 |
