Deep Signature Transforms. - Patrick Kidger; Patric Bonnier; Imanol Pérez Arribas; Cristopher Salvi; Terry J. Lyons (NeurIPS, 2019)

Deep Signatures. - Patric Bonnier; Patrick Kidger; Imanol Pérez Arribas; Cristopher Salvi; Terry J. Lyons (CoRR, 2019)

Universal Approximation with Deep Narrow Networks. - Patrick Kidger; Terry J. Lyons (COLT, 2020)

Neural Controlled Differential Equations for Irregular Time Series. - Patrick Kidger; James Morrill; James Foster; Terry J. Lyons (NeurIPS, 2020)

Generalised Interpretable Shapelets for Irregular Time Series. - Patrick Kidger; James Morrill; Terry J. Lyons (CoRR, 2020)

A Generalised Signature Method for Time Series. - James Morrill; Adeline Fermanian; Patrick Kidger; Terry J. Lyons (CoRR, 2020)

Neural CDEs for Long Time Series via the Log-ODE Method. - James Morrill; Patrick Kidger; Cristopher Salvi; James Foster; Terry J. Lyons (CoRR, 2020)

"Hey, that's not an ODE": Faster ODE Adjoints with 12 Lines of Code. - Patrick Kidger; Ricky T. Q. Chen; Terry J. Lyons (CoRR, 2020)

Signatory: differentiable computations of the signature and logsignature transforms, on both CPU and GPU. - Patrick Kidger; Terry J. Lyons (ICLR, 2021)

"Hey, that's not an ODE": Faster ODE Adjoints via Seminorms. - Patrick Kidger; Ricky T. Q. Chen; Terry J. Lyons (ICML, 2021)

Neural SDEs as Infinite-Dimensional GANs. - Patrick Kidger; James Foster; Xuechen Li; Terry J. Lyons (ICML, 2021)

Neural Rough Differential Equations for Long Time Series. - James Morrill; Cristopher Salvi; Patrick Kidger; James Foster (ICML, 2021)

Efficient and Accurate Gradients for Neural SDEs. - Patrick Kidger; James Foster; Xuechen Li; Terry J. Lyons (NeurIPS, 2021)

Neural SDEs as Infinite-Dimensional GANs. - Patrick Kidger; James Foster; Xuechen Li; Harald Oberhauser; Terry J. Lyons (CoRR, 2021)

Neural Controlled Differential Equations for Online Prediction Tasks. - James Morrill; Patrick Kidger; Lingyi Yang; Terry J. Lyons (CoRR, 2021)

Equinox: neural networks in JAX via callable PyTrees and filtered transformations. - Patrick Kidger; Cristian Garcia (CoRR, 2021)

On Neural Differential Equations. - Patrick Kidger (CoRR, 2022)

On the Choice of Interpolation Scheme for Neural CDEs. - James Morrill; Patrick Kidger; Lingyi Yang; Terry J. Lyons (Trans. Mach. Learn. Res., 2022)

Lineax: unified linear solves and linear least-squares in JAX and Equinox. - Jason Rader; Terry J. Lyons; Patrick Kidger (CoRR, 2023)

Optimistix: modular optimisation in JAX and Equinox. - Jason Rader; Terry J. Lyons; Patrick Kidger (CoRR, 2024)

Single-seed generation of Brownian paths and integrals for adaptive and high order SDE solvers. - Andraz Jelincic; James Foster; Patrick Kidger (CoRR, 2024)

AlgoTune: Can Language Models Speed Up General-Purpose Numerical Programs? - Ori Press; Brandon Amos; Haoyu Zhao; Yikai Wu; Samuel K. Ainsworth; Dominik Krupke; Patrick Kidger; Touqir Sajed; Bartolomeo Stellato; Jisun Park; Nathanael Bosch; Eli Meril; et al. (CoRR, 2025)