| Practical deep learning with Bayesian principles K Osawa, S Swaroop, MEE Khan, A Jain, R Eschenhagen, RE Turner, ... Advances in neural information processing systems 32, 2019 | 285 | 2019 |
| Continual deep learning by functional regularisation of memorable past P Pan, S Swaroop, A Immer, R Eschenhagen, R Turner, MEE Khan Advances in neural information processing systems 33, 4453-4464, 2020 | 145 | 2020 |
| Partitioned variational inference: A unified framework encompassing federated and continual learning TD Bui, CV Nguyen, S Swaroop, RE Turner arXiv preprint arXiv:1811.11206, 2018 | 66 | 2018 |
| Generalized variational continual learning N Loo, S Swaroop, RE Turner International Conference on Learning Representations, 2021 | 65 | 2021 |
| Improving and understanding variational continual learning S Swaroop, CV Nguyen, TD Bui, RE Turner arXiv preprint arXiv:1905.02099, 2019 | 60 | 2019 |
| Efficient low rank gaussian variational inference for neural networks M Tomczak, S Swaroop, R Turner Advances in Neural Information Processing Systems 33, 4610-4622, 2020 | 31 | 2020 |
| Knowledge-adaptation priors MEE Khan, S Swaroop Advances in neural information processing systems 34, 19757-19770, 2021 | 24 | 2021 |
| Collapsed variational bounds for Bayesian neural networks M Tomczak, S Swaroop, A Foong, R Turner Advances in Neural Information Processing Systems 34, 25412-25426, 2021 | 16 | 2021 |
| Neural network ensembles and variational inference revisited MB Tomczak, S Swaroop, RE Turner | 16 | 2018 |
| Partitioned variational inference: A framework for probabilistic federated learning M Ashman, TD Bui, CV Nguyen, S Markou, A Weller, S Swaroop, ... arXiv preprint arXiv:2202.12275, 2022 | 11 | 2022 |
| Towards Optimizing Human-Centric Objectives in AI-Assisted Decision-Making With Offline Reinforcement Learning Z Buçinca, S Swaroop, AE Paluch, SA Murphy, KZ Gajos arXiv preprint arXiv:2403.05911, 2024 | 9 | 2024 |
| Differentially private federated variational inference M Sharma, M Hutchinson, S Swaroop, A Honkela, RE Turner arXiv preprint arXiv:1911.10563, 2019 | 8 | 2019 |
| Accuracy-Time Tradeoffs in AI-Assisted Decision Making under Time Pressure S Swaroop, Z Buçinca, KZ Gajos, F Doshi-Velez Proceedings of the 29th International Conference on Intelligent User …, 2024 | 7 | 2024 |
| Soft prompting might be a bug, not a feature L Bailey, G Ahdritz, A Kleiman, S Swaroop, F Doshi-Velez, W Pan | 7 | 2023 |
| Modeling mobile health users as reinforcement learning agents E Shin, S Swaroop, W Pan, S Murphy, F Doshi-Velez arXiv preprint arXiv:2212.00863, 2022 | 5 | 2022 |
| Discovering User Types: Mapping User Traits by Task-Specific Behaviors in Reinforcement Learning LL Ankile, BS Ham, K Mao, E Shin, S Swaroop, F Doshi-Velez, W Pan arXiv preprint arXiv:2307.08169, 2023 | 3 | 2023 |
| Reinforcement Learning Interventions on Boundedly Rational Human Agents in Frictionful Tasks E Nofshin, S Swaroop, W Pan, S Murphy, F Doshi-Velez arXiv preprint arXiv:2401.14923, 2024 | 2 | 2024 |
| Adaptive interventions for both accuracy and time in AI-assisted human decision making S Swaroop, Z Buçinca, F Doshi-Velez arXiv preprint arXiv:2306.07458, 2023 | 2 | 2023 |
| Combining Variational Continual Learning with FiLM Layers N Loo, S Swaroop, RE Turner 4th Lifelong Machine Learning Workshop at ICML 2020, 2020 | 2 | 2020 |
| Understanding Expectation Propagation S Swaroop, RE Turner Technical report, University of Cambridge, May 2017. URL https://github. com …, 2017 | 2 | 2017 |
Richard E TurnerProfessor, University of Cambridge在 cam.ac.uk 的电子邮件经过验证
