| Epileptic Seizure Classification with Symmetric and Hybrid Bilinear Models T Liu, ND Truong, A Nikpour, L Zhou, O Kavehei IEEE Journal of Biomedical and Health Informatics 24 (10), 2844-2851, 2020 | 64 | 2020 |
| Hyperimpute: Generalized Iterative Imputation with Automatic Model Selection D Jarrett, BC Cebere, T Liu, A Curth, M van der Schaar International Conference on Machine Learning, 9916-9937, 2022 | 50 | 2022 |
| 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, 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 International Conference on Learning Representations, 2023 | 18 | 2023 |
| Large Language Models to Enhance Bayesian Optimization T Liu*, N Astorga*, N Seedat, M van der Schaar The Twelfth International Conference on Learning Representations, 2024 | 15 | 2024 |
| Joint Training of Deep Ensembles Fails Due to Learner Collusion A Jeffares, T Liu, J Crabbé, M van der Schaar Neural Information Processing Systems (NeurIPS), 2023 | 12 | 2023 |
| Practical Approaches for Fair Learning with Multitype and Multivariate Sensitive Attributes T Liu, AJ Chan, B van Breugel, M van der Schaar Algorithmic Fairness through the Lens of Causality and Privacy at NeurIPS 2022, 2022 | 2 | 2022 |
| Learning Representations Without Compositional Assumptions T Liu, J Berrevoets, Z Qian, M Van Der Schaar International Conference on Machine Learning, 21388-21403, 2023 | 1 | 2023 |
| Unveiling the Power of Sparse Neural Networks for Feature Selection Z Atashgahi, T Liu, M Pechenizkiy, R Veldhuis, DC Mocanu, ... arXiv preprint arXiv:2408.04583, 2024 | | 2024 |
| Towards Transparent Time Series Forecasting K Kacprzyk, T Liu, M van der Schaar The Twelfth International Conference on Learning Representations, 2024 | | 2024 |
