How faithful is your synthetic data? sample-level metrics for evaluating and auditing generative models A Alaa, B Van Breugel, ES Saveliev, M van der Schaar International Conference on Machine Learning, 290-306, 2022 | 122 | 2022 |
Instructions and guide for diagnostic questions: The neurips 2020 education challenge Z Wang, A Lamb, E Saveliev, P Cameron, Y Zaykov, ... arXiv preprint arXiv:2007.12061, 2020 | 66 | 2020 |
Hide-and-seek privacy challenge: Synthetic data generation vs. patient re-identification J Jordon, D Jarrett, E Saveliev, J Yoon, P Elbers, P Thoral, A Ercole, ... NeurIPS 2020 Competition and Demonstration Track, 206-215, 2021 | 39 | 2021 |
Results and insights from diagnostic questions: The neurips 2020 education challenge Z Wang, A Lamb, E Saveliev, P Cameron, J Zaykov, ... NeurIPS 2020 Competition and Demonstration Track, 191-205, 2021 | 15 | 2021 |
Developing machine learning algorithms for dynamic estimation of progression during active surveillance for prostate cancer C Lee, A Light, ES Saveliev, M Van der Schaar, VJ Gnanapragasam NPJ digital medicine 5 (1), 110, 2022 | 10 | 2022 |
How faithful is your synthetic data AM Alaa, B van Breugel, E Saveliev, M van der Schaar Sample-Level Metrics for Evaluating and Auditing Generative Models. arXiv, 2022 | 7 | 2022 |
Contextual HyperNetworks for Novel Feature Adaptation CZ Angus Lamb, Evgeny Saveliev, Yingzhen Li, Sebastian Tschiatschek, Camilla ... NeurIPS Workshop on Meta-Learning, 2020 | 5* | 2020 |
Auxiliary model for predicting new model parameters C Zhang, L Angus, ES Saveliev, LI Yingzhen, C Longden, P Cameron, ... US Patent App. 17/095,700, 2022 | 3 | 2022 |
Temporai: Facilitating machine learning innovation in time domain tasks for medicine ES Saveliev, M van der Schaar arXiv preprint arXiv:2301.12260, 2023 | 2 | 2023 |
Machine learning tackles the problem of dynamic disease progression in prostate cancer patients E Saveliev | | |