| 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 | 576 | 2020 |
| Universal approximation with deep narrow networks P Kidger, T Lyons Conference on Learning Theory, 2306-2327, 2020 | 464 | 2020 |
| On Neural Differential Equations P Kidger Doctoral Thesis, 2022 | 368 | 2022 |
| Neural SDEs as Infinite-Dimensional GANs P Kidger, J Foster, X Li, H Oberhauser, T Lyons International Conference on Machine Learning, 2021 | 174 | 2021 |
| Neural Rough Differential Equations for Long Time Series J Morrill, C Salvi, P Kidger, J Foster, T Lyons International Conference on Machine Learning, 2021 | 171* | 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 | 121 | 2021 |
| Deep signature transforms P Kidger, P Bonnier, I Perez Arribas, C Salvi, T Lyons Advances in Neural Information Processing Systems 32, 3105-3115, 2019 | 114 | 2019 |
| Equinox: neural networks in JAX via callable PyTrees and filtered transformations P Kidger, C Garcia Differentiable Programming workshop, Neural Information Processing Systems 2021, 2021 | 112 | 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 | 73* | 2020 |
| “Hey, that’s not an ODE”: Faster ODE Adjoints via Seminorms P Kidger, RTQ Chen, T Lyons International Conference on Machine Learning, 2021 | 69* | 2021 |
| Efficient and Accurate Gradients for Neural SDEs P Kidger, J Foster, X Li, T Lyons Advances in Neural Information Processing Systems 34, 2021 | 58 | 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 | 52* | 2022 |
| Generalised Interpretable Shapelets for Irregular Time Series P Kidger, J Morrill, T Lyons arXiv preprint arXiv:2005.13948, 2020 | 13 | 2020 |
| Optimistix: modular optimisation in JAX and Equinox J Rader, T Lyons, P Kidger arXiv preprint arXiv:2402.09983, 2024 | 6 | 2024 |
| 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 | 4 | 2023 |
| Single-seed generation of Brownian paths and integrals for adaptive and high order SDE solvers A Jelinčič, J Foster, P Kidger arXiv preprint arXiv:2405.06464, 2024 | 2 | 2024 |
| AIntibody: an experimentally validated in silico antibody discovery design challenge MF Erasmus, L Spector, F Ferrara, R DiNiro, TJ Pohl, K Perea-Schmittle, ... Nature Biotechnology, 1-6, 2024 | 1 | 2024 |
| Learning constitutive relations from soil moisture data via physically constrained neural networks T Bandai, TA Ghezzehei, P Jiang, P Kidger, X Chen, CI Steefel Water Resources Research 60 (7), e2024WR037318, 2024 | 1 | 2024 |
| Differentiable Land Surface Modeling Using JAX P Jiang, P Kidger, G Bisht, T Bandai, KG Pressel, CI Steefel, X Chen AGU Fall Meeting Abstracts 2023, H22B-06, 2023 | | 2023 |
James MorrillPhD Student, University of OxfordVerified email at maths.ox.ac.uk