Learning overlapping representations for the estimation of individualized treatment effects Y Zhang, A Bellot, M Schaar AISTATS 2020, 2020 | 94 | 2020 |
Predicting the risk of inpatient hypoglycemia with machine learning using electronic health records Y Ruan, A Bellot, Z Moysova, GD Tan, A Lumb, J Davies, ... Diabetes care 43 (7), 1504-1511, 2020 | 68 | 2020 |
Conditional independence testing using generative adversarial networks A Bellot, M van der Schaar NeurIPS 2019, 2019 | 53 | 2019 |
Accounting for unobserved confounding in domain generalization A Bellot, M van der Schaar arXiv preprint arXiv:2007.10653, 2020 | 41* | 2020 |
Miracle: Causally-aware imputation via learning missing data mechanisms T Kyono, Y Zhang, A Bellot, M van der Schaar NeurIPS 2021, 2021 | 39 | 2021 |
Continuous-time modeling of counterfactual outcomes using neural controlled differential equations N Seedat, F Imrie, A Bellot, Z Qian, M van der Schaar ICML 2022, 2022 | 33 | 2022 |
Neural graphical modelling in continuous-time: consistency guarantees and algorithms A Bellot, K Branson, M van der Schaar ICLR 2022, 2021 | 27* | 2021 |
Logistic regression and machine learning predicted patient mortality from large sets of diagnosis codes comparably TE Cowling, DA Cromwell, A Bellot, LD Sharples, J van der Meulen Journal of Clinical Epidemiology 133, 43-52, 2021 | 25 | 2021 |
Learning dynamic and personalized comorbidity networks from event data using deep diffusion processes Z Qian, A Alaa, A Bellot, M Schaar, J Rashbass AISTATS 2020, 2020 | 22 | 2020 |
Tree-based bayesian mixture model for competing risks A Bellot, M Schaar AISTATS 2018, 2018 | 19 | 2018 |
Multitask boosting for survival analysis with competing risks A Bellot, M van der Schaar NeurIPS 2018, 2018 | 19 | 2018 |
Policy Analysis using Synthetic Controls in Continuous-Time A Bellot, M van der Schaar ICML 2021, 2021 | 18 | 2021 |
Boosted trees for risk prognosis A Bellot, M van der Schaar Machine Learning for Healthcare Conference, 2-16, 2018 | 18 | 2018 |
A hierarchical bayesian model for personalized survival predictions A Bellot, M Van der Schaar IEEE journal of biomedical and health informatics 23 (1), 72-80, 2018 | 15 | 2018 |
Boosting transfer learning with survival data from heterogeneous domains A Bellot, M van der Schaar AISTATS 2019, 2019 | 13 | 2019 |
Flexible modelling of longitudinal medical data: A Bayesian nonparametric approach A Bellot, MVD Schaar ACM Transactions on Computing for Healthcare 1 (1), 1-15, 2020 | 10 | 2020 |
Linear Deconfounded Score Method: Scoring DAGs With Dense Unobserved Confounding A Bellot, M van der Schaar IEEE Transactions on Neural Networks and Learning Systems, 2024 | 8* | 2024 |
Generalization bounds and algorithms for estimating conditional average treatment effect of dosage A Bellot, A Dhir, G Prando arXiv preprint arXiv:2205.14692, 2022 | 8 | 2022 |
Scores for learning discrete causal graphs with unobserved confounders A Bellot, J Zhang, E Bareinboim AAAI 2024, 2024 | 5 | 2024 |
Continual causality: A retrospective of the inaugural aaai-23 bridge program M Mundt, KW Cooper, DS Dhami, A Ribeiro, JS Smith, A Bellot, T Hayes AAAI Bridge Program on Continual Causality, 1-10, 2023 | 4 | 2023 |