| Scalable Bayesian Inverse Reinforcement Learning AJ Chan, M van der Schaar International Conference on Learning Representations (ICLR), 2021 | 54 | 2021 |
| Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift AJ Chan, AM Alaa, Z Qian, M van der Schaar International Conference on Machine Learning (ICML), 2020 | 40 | 2020 |
| Generative Time-Series Modeling with Fourier Flows AM Alaa, AJ Chan, M van der Schaar International Conference on Learning Representations (ICLR), 2021 | 33 | 2021 |
| GAUCHE: A Library for Gaussian Processes in Chemistry RR Griffiths, L Klarner, H Moss, A Ravuri, ST Truong, B Rankovic, Y Du, ... Advances in Neural Information Processing Systems (NeurIPS), 2023 | 25* | 2023 |
| POETREE: Interpretable Policy Learning with Adaptive Decision Trees A Pace, AJ Chan, M van der Schaar International Conference on Learning Representations (ICLR), 2022 | 21 | 2022 |
| The Medkit-Learn (ing) Environment: Medical Decision Modelling through Simulation AJ Chan, I Bica, A Huyuk, D Jarrett, M van der Schaar Neural Information Processing Systems (NeurIPS) track on Datasets and Benchmarks, 2021 | 15 | 2021 |
| How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions L Pacchiardi*, AJ Chan*, S Mindermann, I Moscovitz, AY Pan, Y Gal, ... International Conference on Learning Representations (ICLR), 2024 | 13 | 2024 |
| Inverse Online Learning: Understanding Non-Stationary and Reactionary Policies AJ Chan, A Curth, M van der Schaar International Conference on Learning Representations (ICLR), 2022 | 6 | 2022 |
| Synthetic Model Combination: A new machine learning method for pharmacometric model ensembling AJ Chan, R Peck, M Gibbs, M van der Schaar CPT: Pharmacometrics & Systems Pharmacology, 2023 | 3 | 2023 |
| Dense Reward for Free in Reinforcement Learning from Human Feedback AJ Chan, H Sun, S Holt, M van der Schaar International Conference on Machine Learning (ICML), 2024 | 2 | 2024 |
| 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, 2022 | 2 | 2022 |
| Interpretable Policy Learning AJ Chan University of Cambridge, 2020 | 2 | 2020 |
| Harmonizing Global Voices: Culturally-Aware Models for Enhanced Content Moderation AJ Chan, JLR García, F Silvestri, C O'Donnel, K Palla arXiv preprint arXiv:2312.02401, 2023 | 1 | 2023 |
| When is Off-Policy Evaluation Useful? A Data-Centric Perspective H Sun, AJ Chan, N Seedat, A Hüyük, M van der Schaar arXiv preprint arXiv:2311.14110, 2023 | 1 | 2023 |
| Optimising Human-AI Collaboration by Learning Convincing Explanations AJ Chan, A Hüyük, M van der Schaar XAI in Action: Past, Present, and Future Applications, 2023 | 1 | 2023 |
| AllSim: Simulating and Benchmarking Resource Allocation Policies in Multi-User Systems J Berrevoets, D Jarrett, AJ Chan, M van der Schaar Neural Information Processing Systems (NeurIPS) track on Datasets and Benchmarks, 2023 | 1 | 2023 |
| Synthetic Model Combination: An Instance-wise Approach to Unsupervised Ensemble Learning AJ Chan, M van der Schaar Advances in Neural Information Processing Systems (NeurIPS), 2022 | 1 | 2022 |
| Probabilistic Deep Learning AJ Chan University College London, 2019 | | 2019 |
Mihaela van der SchaarUniversity of Cambridge, The Alan Turing Institute在 ee.ucla.edu 的电子邮件经过验证
