On feature collapse and deep kernel learning for single forward pass uncertainty J van Amersfoort, L Smith, A Jesson, O Key, Y Gal
arXiv preprint arXiv:2102.11409, 2021
167 * 2021 Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties L Schut, O Key, R Mc Grath, L Costabello, B Sacaleanu, Y Gal
International Conference on Artificial Intelligence and Statistics, 1756-1764, 2021
57 2021 No train no gain: Revisiting efficient training algorithms for transformer-based language models J Kaddour, O Key, P Nawrot, P Minervini, MJ Kusner
Advances in Neural Information Processing Systems 36, 2024
30 2024 Interlocking Backpropagation: Improving depthwise model-parallelism AN Gomez, O Key, K Perlin, S Gou, N Frosst, J Dean, Y Gal
Journal of Machine Learning Research 23 (171), 1-28, 2022
23 2022 Composite goodness-of-fit tests with kernels O Key, A Gretton, FX Briol, T Fernandez
arXiv preprint arXiv:2111.10275, 2021
17 2021 Towards Healing the Blindness of Score Matching M Zhang, O Key, P Hayes, D Barber, B Paige, FX Briol
arXiv preprint arXiv:2209.07396, 2022
15 2022 Optimally-weighted estimators of the maximum mean discrepancy for likelihood-free inference A Bharti, M Naslidnyk, O Key, S Kaski, FX Briol
International Conference on Machine Learning, 2289-2312, 2023
12 2023 On signal-to-noise ratio issues in variational inference for deep Gaussian processes TGJ Rudner, O Key, Y Gal, T Rainforth
International Conference on Machine Learning, 9148-9156, 2021
3 2021 Scalable data assimilation with message passing O Key, S Takao, D Giles, MP Deisenroth
Environmental Data Science 4, e1, 2025
2025 Approximate Top- O Key, L Ribar, A Cattaneo, L Hudlass-Galley, D Orr
arXiv preprint arXiv:2412.04358, 2024
2024 