| Inferring the effectiveness of government interventions against COVID-19 JM Brauner, S Mindermann, M Sharma, D Johnston, J Salvatier, ... Science 371 (6531), 2021 | 1031 | 2021 |
| Turing: a language for flexible probabilistic inference H Ge, K Xu, Z Ghahramani Proceedings of the Twenty-First International Conference on Artificial …, 2018 | 423 | 2018 |
| Transcriptional data: a new gateway to drug repositioning? F Iorio, H Ge, T Rittman, M Menden, J Saez-Rodriguez Drug discovery today 18 (7), 350-357, 2013 | 276 | 2013 |
| The effectiveness of eight nonpharmaceutical interventions against COVID-19 in 41 countries JM Brauner, S Mindermann, M Sharma, AB Stephenson, T Gavenčiak, ... MedRxiv, 2020 | 123* | 2020 |
| Bayesian learning of sum-product networks M Trapp, R Peharz, H Ge, F Pernkopf, Z Ghahramani Advances in Neural Information Processing Systems, 6347-6358, 2019 | 53 | 2019 |
| Distributed Inference for Dirichlet Process Mixture Models H Ge, Y Chen, M Wang, Z Ghahramani The 32nd International Conference on Machine Learning, 2276-2284, 2015 | 46 | 2015 |
| AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms K Xu, H Ge, W Tebbutt, M Tarek, M Trapp, Z Ghahramani Symposium on Advances in Approximate Bayesian Inference, 2019 | 36* | 2019 |
| A Bayesian model for calibrating conference review scores H Ge, M Welling, Z Ghahramani http://mlg.eng.cam.ac.uk/hong/unpublished/nips-review-model.pdf, 2013 | 33* | 2013 |
| Particle Gibbs for Infinite Hidden Markov Models N Tripuraneni, S Gu, H Ge, Z Ghahramani Advances in Neural Information Processing Systems, 2395-2403, 2015 | 27 | 2015 |
| Interoperability of statistical models in pandemic preparedness: principles and reality G Nicholson, M Blangiardo, M Briers, PJ Diggle, TE Fjelde, H Ge, ... Statistical Science 37 (2), 183-206, 2022 | 19 | 2022 |
| DynamicPPL: Stan-like speed for dynamic probabilistic models M Tarek, K Xu, M Trapp, H Ge, Z Ghahramani arXiv preprint arXiv:2002.02702, 2020 | 17* | 2020 |
| Couplings for Multinomial Hamiltonian Monte Carlo K Xu, TE Fjelde, C Sutton, H Ge International Conference on Artificial Intelligence and Statistics, 3646-3654, 2021 | 15 | 2021 |
| Beyond intuition, a framework for applying GPs to real-world data K Tazi, JA Lin, R Viljoen, A Gardner, ST John, H Ge, RE Turner arXiv preprint arXiv:2307.03093, 2023 | 3 | 2023 |
| Multi-Objective Bayesian Optimization for Design of Pareto-Optimal Current Drive Profiles in STEP T Brown, S Marsden, V Gopakumar, A Terenin, H Ge, F Casson IEEE Transactions on Plasma Science, 2024 | 2 | 2024 |
| Numerically stable sparse gaussian processes via minimum separation using cover trees A Terenin, DR Burt, A Artemev, S Flaxman, M van der Wilk, ... Journal of Machine Learning Research 25, 1-36, 2024 | 2 | 2024 |
| Towards more interpretable and robust geospatial modelling with Gaussian Processes K Tazi, JA Lin, AS Gardner, ST John, H Ge, RE Turner AGU Fall Meeting Abstracts 2023 (563), IN11C-0563, 2023 | 1 | 2023 |
| Practical Hamiltonian Monte Carlo on Riemannian Manifolds via Relativity Theory K Xu, H Ge Forty-first International Conference on Machine Learning, 2024 | | 2024 |
| Bayesian inference and neural estimation of acoustic wave propagation Y Huang, Y He, H Ge arXiv preprint arXiv:2305.17749, 2023 | | 2023 |
| ReLU Characteristic Activation Analysis W Chen, H Ge arXiv preprint arXiv:2305.15912, 2023 | | 2023 |
| Understanding Sparse Feature Updates in Deep Networks using Iterative Linearisation A Goldwaser, H Ge arXiv preprint arXiv:2211.12345, 2022 | | 2022 |
Zoubin GhahramaniProfessor, University of Cambridge, and Distinguished Researcher, GoogleDirección de correo verificada de eng.cam.ac.uk
