| DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks B van Breugel*, T Kyono*, J Berrevoets, M van der Schaar Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 80 | 2021 |
| Improving workflow efficiency for mammography using machine learning T Kyono, FJ Gilbert, M van der Schaar Journal of the American College of Radiology 17 (1), 56-63, 2020 | 78 | 2020 |
| CASTLE: Regularization via Auxiliary Causal Graph Discovery T Kyono, Y Zhang, M van der Schaar Advances in Neural Information Processing Systems (NeurIPS), 2020 | 67 | 2020 |
| MIRACLE: Causally-Aware Imputation via Learning Missing Data Mechanisms T Kyono, Y Zhang, A Bellot, M van der Schaar Advances in Neural Information Processing Systems (NeurIPS) 34, 2021 | 45 | 2021 |
| Triage of 2d mammographic images using multi-view multi-task convolutional neural networks T Kyono, FJ Gilbert, MVD Schaar ACM Transactions on Computing for Healthcare 2 (3), 1-24, 2021 | 45* | 2021 |
| Machine learning for quality assessment of ground-based optical images of satellites T Kyono, J Lucas, M Werth, B Calef, I McQuaid, J Fletcher Optical Engineering 59 (5), 051403-051403, 2020 | 22 | 2020 |
| Multi-view multi-task learning for improving autonomous mammogram diagnosis T Kyono, FJ Gilbert, M Schaar Machine Learning for Healthcare Conference, 571-591, 2019 | 18 | 2019 |
| To impute or not to impute? missing data in treatment effect estimation J Berrevoets, F Imrie, T Kyono, J Jordon, M Van der Schaar International Conference on Artificial Intelligence and Statistics, 3568-3590, 2023 | 17 | 2023 |
| Commentator: A front-end user-interface module for graphical and structural equation modeling T Kyono University of California, Los Angeles (Thesis under Judea Pearl), 2010 | 16 | 2010 |
| Formal analysis of neural network-based systems in the aircraft domain P Kouvaros, T Kyono, F Leofante, A Lomuscio, D Margineantu, ... Formal Methods: 24th International Symposium, FM 2021, Virtual Event …, 2021 | 15 | 2021 |
| Selecting treatment effects models for domain adaptation using causal knowledge T Kyono, I Bica, Z Qian, M van der Schaar ACM Transactions on Computing for Healthcare 4 (2), 1-29, 2023 | 11 | 2023 |
| Exploiting causal structure for robust model selection in unsupervised domain adaptation T Kyono, M Van der Schaar IEEE Transactions on Artificial Intelligence 2 (6), 494-507, 2021 | 11 | 2021 |
| Silo: A machine learning dataset of synthetic ground-based observations of leo satellites M Werth, J Lucas, T Kyono, I McQuaid, J Fletcher 2020 IEEE Aerospace Conference, 1-8, 2020 | 11 | 2020 |
| Improving model robustness using causal knowledge T Kyono, M van der Schaar arXiv preprint arXiv:1911.12441, 2019 | 11 | 2019 |
| Recovering astronomical images with deep neural network supported bispectrum processing J Lucas, B Calef, T Kyono Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference, 2018 | 11 | 2018 |
| Automated interpretability scoring of ground-based observations of leo objects with deep learning J Lucas, M Werth, T Kyono, I Mcquaid, J Fletcher 2020 IEEE Aerospace Conference, 1-7, 2020 | 10 | 2020 |
| Determining Multi-frame Blind Deconvolution Resolvability using Deep Learning T Kyono, J Lucas, M Werth, J Flecther, I McQuaid Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference, 62, 2019 | 9 | 2019 |
| Estimating Satellite Orientation through Turbulence with Deep Learning J Lucas, T Kyono, M Werth, N Gagnier, Z Endsley, J Fletcher, I McQuaid Advanced Maui Optical and Space Surveillance Technologies (AMOS) Conference, 2020 | 7 | 2020 |
| Siamese survival analysis with competing risks A Nemchenko, T Kyono, M Van Der Schaar Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018 | 7 | 2018 |
| Quality-Weighted Iterative Deconvolution (QWID) M Werth, T Kyono, J Lucas, J Fletcher, I Mcquaid, M Brannon Advanced Maui Optical and Space Surveillance (AMOS) Technologies Conference, 2020 | 6 | 2020 |
Mihaela van der SchaarUniversity of Cambridge, The Alan Turing Institute在 ee.ucla.edu 的电子邮件经过验证
