| Why you should stop predicting customer churn and start using uplift models F Devriendt, J Berrevoets, W Verbeke Information Sciences, 2021 | 115 | 2021 |
| DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks B van Breugel*, T Kyono*, J Berrevoets, M van der Schaar Neural Information Processing Systems (NeurIPS), 2021 | 105 | 2021 |
| GOGGLE: Generative Modelling for Tabular Data by Learning Relational Structure T Liu, Z Qian, J Berrevoets, M van der Schaar International Conference on Learning Representations (ICLR), 2023 | 50 | 2023 |
| OrganITE: Optimal transplant donor organ offering using an individual treatment effect J Berrevoets, J Jordon, I Bica, A Gimson, M van der Schaar Neural Information Processing Systems (NeurIPS), 2020 | 45 | 2020 |
| Causal deep learning J Berrevoets, K Kacprzyk, Z Qian, M van der Schaar arXiv preprint arXiv:2303.02186, 2023 | 30 | 2023 |
| Combining observational and randomized data for estimating heterogeneous treatment effects T Hatt, J Berrevoets, A Curth, S Feuerriegel, M van der Schaar arXiv preprint arXiv:2202.12891, 2022 | 27 | 2022 |
| 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 | 23 | 2023 |
| Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis J Berrevoets, A Alaa, Z Qian, J Jordon, AES Gimson, M Van Der Schaar International Conference on Machine Learning (ICML), 2021 | 20 | 2021 |
| The foundations of cost-sensitive causal classification W Verbeke, D Olaya, J Berrevoets, S Verboven, S Maldonado arXiv preprint arXiv:2007.12582, 2020 | 17 | 2020 |
| Autoencoders for strategic decision support S Verboven, J Berrevoets, C Wuytens, B Baesens, W Verbeke Decision Support Systems, 2020 | 16 | 2020 |
| Hydalearn: Highly dynamic task weighting for multitask learning with auxiliary tasks S Verboven, MH Chaudhary, J Berrevoets, V Ginis, W Verbeke Applied Intelligence 53 (5), 5808-5822, 2023 | 14 | 2023 |
| Disentangled counterfactual recurrent networks for treatment effect inference over time J Berrevoets, A Curth, I Bica, E McKinney, M van der Schaar arXiv preprint arXiv:2112.03811, 2021 | 14 | 2021 |
| Treatment effect optimisation in dynamic environments J Berrevoets, S Verboven, W Verbeke Journal of Causal Inference 10 (1), 106-122, 2022 | 10 | 2022 |
| Identifiable Energy-based Representations: An Application to Estimating Heterogeneous Causal Effects Y Zhang*, J Berrevoets*, M van der Schaar International Conference on Artificial Intelligence and Statistics (AISTATS), 2022 | 8 | 2022 |
| NOFLITE: Learning to Predict Individual Treatment Effect Distributions T Vanderschueren, J Berrevoets, W Verbeke Transactions on Machine Learning Research (TMLR), 2023 | 6 | 2023 |
| Optimising Individual-Treatment-Effect Using Bandits J Berrevoets, S Verboven, W Verbeke CausalML Workshop at Neural Information Processing Systems, 2019 | 6 | 2019 |
| AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems J Berrevoets, D Jarrett, A Chan, M van der Schaar Neural Information Processing Systems (NeurIPS), 2023 | 3 | 2023 |
| DAGnosis: Localized Identification of Data Inconsistencies using Structures N Huynh*, J Berrevoets*, N Seedat, J Crabbé, Z Qian, M van der Schaar International Conference on Artificial Intelligence and Statistics (AISTATS), 2024 | 2 | 2024 |
| ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference K Kacprzyk*, S Holt*, J Berrevoets*, Z Qian, M van der Schaar International Conference on Learning Representations (ICLR), 2024 | 2 | 2024 |
| Differentiable and Transportable Structure Learning J Berrevoets, N Seedat, F Imrie, M van der Schaar International Conference on Machine Learning (ICML), 2023 | 2 | 2023 |
Mihaela van der SchaarUniversity of Cambridge, The Alan Turing Institute在 ee.ucla.edu 的电子邮件经过验证
