| Deep generative models for 3d linker design F Imrie, AR Bradley, M van der Schaar, CM Deane Journal of chemical information and modeling 60 (4), 1983-1995, 2020 | 226 | 2020 |
| Protein family-specific models using deep neural networks and transfer learning improve virtual screening and highlight the need for more data F Imrie, AR Bradley, M van der Schaar, CM Deane Journal of chemical information and modeling 58 (11), 2319-2330, 2018 | 132 | 2018 |
| Deep Generative Design with 3D Pharmacophoric Constraints F Imrie, TE Hadfield, AR Bradley, CM Deane Chemical Science 12, 14577-14589, 2021 | 81 | 2021 |
| Generating property-matched decoy molecules using deep learning F Imrie, AR Bradley, CM Deane Bioinformatics 37 (15), 2134-2141, 2021 | 67 | 2021 |
| Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations N Seedat*, F Imrie*, A Bellot, Z Qian, M van der Schaar International Conference on Machine Learning 39, 2022 | 58 | 2022 |
| Explaining Latent Representations with a Corpus of Examples J Crabbé, Z Qian, F Imrie, M van der Schaar Advances in Neural Information Processing Systems 34, 2021 | 47 | 2021 |
| Testing the limits of SMILES-based de novo molecular generation with curriculum and deep reinforcement learning M Mokaya, F Imrie, WP van Hoorn, A Kalisz, AR Bradley, CM Deane Nature Machine Intelligence 5 (4), 386-394, 2023 | 38 | 2023 |
| Navigating Data-Centric Artificial Intelligence with DC-Check: Advances, Challenges, and Opportunities N Seedat, F Imrie, M van der Schaar IEEE Transactions on Artificial Intelligence, 2023 | 35* | 2023 |
| TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization A Jeffares*, T Liu*, J Crabbé, F Imrie, M van der Schaar The Eleventh International Conference on Learning Representations, 2023 | 33 | 2023 |
| AutoPrognosis 2.0: Democratizing diagnostic and prognostic modeling in healthcare with automated machine learning F Imrie, B Cebere, EF McKinney, M van der Schaar PLOS Digital Health 2 (6), e0000276, 2023 | 32 | 2023 |
| Multiple stakeholders drive diverse interpretability requirements for machine learning in healthcare F Imrie, R Davis, M van der Schaar Nature Machine Intelligence 5 (8), 824-829, 2023 | 30 | 2023 |
| 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 (AISTATS), 2023 | 27 | 2023 |
| Self-Supervision Enhanced Feature Selection with Correlated Gates C Lee*, F Imrie*, M van der Schaar International Conference on Learning Representations, 2022 | 25 | 2022 |
| Can You Rely on Your Model Evaluation? Improving Model Evaluation with Synthetic Test Data B van Breugel*, N Seedat*, F Imrie, M van der Schaar Advances in Neural Information Processing Systems 36, 2023 | 19 | 2023 |
| Incorporating target-specific pharmacophoric information into deep generative models for fragment elaboration TE Hadfield, F Imrie, A Merritt, K Birchall, CM Deane Journal of chemical information and modeling 62 (10), 2280-2292, 2022 | 19 | 2022 |
| SurvivalGAN: Generating Time-to-Event Data for Survival Analysis A Norcliffe*, B Cebere*, F Imrie, P Lio, M van der Schaar International Conference on Artificial Intelligence and Statistics (AISTATS), 2023 | 18 | 2023 |
| Improving Adaptive Conformal Prediction Using Self-Supervised Learning N Seedat*, A Jeffares*, F Imrie, M van der Schaar International Conference on Artificial Intelligence and Statistics (AISTATS), 2023 | 17 | 2023 |
| Dissecting sample hardness: A fine-grained analysis of Hardness Characterization Methods for data-centric AI N Seedat, F Imrie, M van der Schaar The Twelfth International Conference on Learning Representations, 2024 | 13 | 2024 |
| Assessing eligibility for lung cancer screening using parsimonious ensemble machine learning models: A development and validation study T Callender, F Imrie, B Cebere, N Pashayan, N Navani, M van der Schaar, ... PLOS Medicine 20 (10), e1004287, 2023 | 13* | 2023 |
| Machine learning with requirements: A manifesto E Giunchiglia, F Imrie, M van der Schaar, T Lukasiewicz Neurosymbolic Artificial Intelligence, 1-13, 2024 | 12 | 2024 |
Mihaela van der SchaarUniversity of Cambridge, The Alan Turing InstituteBestätigte E-Mail-Adresse bei ee.ucla.edu
