| Neural Controlled Differential Equations for Irregular Time Series P Kidger, J Morrill, J Foster, T Lyons Advances in Neural Information Processing Systems 33, 6696--6707, 2020 | 444 | 2020 |
| Universal approximation with deep narrow networks P Kidger, T Lyons Conference on Learning Theory, 2306-2327, 2020 | 371 | 2020 |
| On Neural Differential Equations P Kidger Doctoral Thesis, 2022 | 210 | 2022 |
| Deep signature transforms P Kidger, P Bonnier, I Perez Arribas, C Salvi, T Lyons Advances in Neural Information Processing Systems 32, 3105-3115, 2019 | 140 | 2019 |
| Neural Rough Differential Equations for Long Time Series J Morrill, C Salvi, P Kidger, J Foster, T Lyons International Conference on Machine Learning, 2021 | 129* | 2021 |
| Neural SDEs as Infinite-Dimensional GANs P Kidger, J Foster, X Li, H Oberhauser, T Lyons International Conference on Machine Learning, 2021 | 129 | 2021 |
| Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU P Kidger, T Lyons International Conference on Learning Representations, 2021 | 97 | 2021 |
| A Generalised Signature Method for Multivariate Time Series Feature Extraction J Morrill, A Fermanian, P Kidger, T Lyons arXiv preprint arXiv:2006.00873, 2020 | 54* | 2020 |
| Equinox: neural networks in JAX via callable PyTrees and filtered transformations P Kidger, C Garcia Differentiable Programming workshop, Neural Information Processing Systems 2021, 2021 | 51 | 2021 |
| “Hey, that’s not an ODE”: Faster ODE Adjoints via Seminorms P Kidger, RTQ Chen, T Lyons International Conference on Machine Learning, 2021 | 51* | 2021 |
| On the choice of interpolation scheme for neural CDEs J Morrill, P Kidger, L Yang, T Lyons Transactions on Machine Learning Research 2022 (9), 2022 | 46* | 2022 |
| Efficient and Accurate Gradients for Neural SDEs P Kidger, J Foster, X Li, T Lyons Advances in Neural Information Processing Systems 34, 2021 | 44 | 2021 |
| Generalised Interpretable Shapelets for Irregular Time Series P Kidger, J Morrill, T Lyons arXiv preprint arXiv:2005.13948, 2020 | 11 | 2020 |
| Optimistix: modular optimisation in JAX and Equinox J Rader, T Lyons, P Kidger arXiv preprint arXiv:2402.09983, 2024 | 1 | 2024 |
| Differentiable Land Surface Modeling Using JAX P Jiang, P Kidger, G Bisht, T Bandai, KG Pressel, CI Steefel, X Chen AGU23, 2023 | | 2023 |
| Lineax: unified linear solves and linear least-squares in JAX and Equinox JM Rader, T Lyons, P Kidger NeurIPS 2023 AI for Science Workshop, 2023 | | 2023 |
James MorrillPhD Student, University of Oxford在 maths.ox.ac.uk 的电子邮件经过验证
