Preprints and publications

Preprints and publications


O. Sheridan-Methven, M.B. Giles
Rounding error using low precision approximate random variables
SIAM Journal of Scientific Computing to appear 2024



M.B. Giles

Approximation of an inverse of the incomplete beta function. Proceedings of International Congress on Mathematical Software 2024

To appear in the Springer  series Lecture notes in Computer Science (LNCS)




Talia Tseriotou, Ryan Sze-Yin Chan, Adam Tsakalidis, Iman Munire Bilal , Elena Kochkina, Terry Lyons, Maria Liakata
Sig-Networks Toolkit: Signature Networks for Longitudinal Language Modelling


Jason Rader, Terry Lyons, Patrick Kidger
Lineax: unified linear solves and linear least-squares in JAX and Equinox


Karl Welzel, Raphael A Hauser 
Approximating Higher-Order Derivative Tensors Using Secant Updates

SIAM Journal on Optimization (SIOPT), 2024

Wenqing Ouyang, Yang Liu, Andre Milzarek
Descent Properties of an Anderson Accelerated Gradient Method With Restarting

Accepted to appear in SIAM Journal on Optimization (SIOPT)

Ahmed Ammar Naseer, Benjamin Walker, Christopher Landon, Andrew Ambrosy, Marat Fudim, Nicholas Wysham, Botros Toro, Sumanth Swaminathan, Terry Lyons
ScoEHR: Generating Synthetic Electronic Health Records using Continuous-time Diffusion Models

Machine Learning for Healthcare, 2023

Coralia Cartis, Wenqi Zhu
Second-order methods for quartically-regularised cubic polynomials, with applications to high-order tensor methods


Michael Giles, Oliver Sheridan-Methven
Approximating inverse cumulative distribution functions to produce approximate random variables
ACM TOMS, 2023

Michael Giles
Monte Carlo and Quasi-Monte Carlo Methods
MCQMC, 2022

Giuseppe Ughi, Jared Tanner
Mutual information of neural network initializations: a random matrix theory study
(In review)

Rasheed Ibraheem, Yue Wu, Terry Lyons, Goncalo dos Reis
Early prediction of Lithium-ion cell degradation trajectories using signatures of voltage curves up to 4-minute sub-sampling rates

Youness Boutaib, Terry Lyons
A new definition of rough paths on manifolds
Annales de la Faculte des sciences de Toulouse, 2022

Yue Wu, Guy M. Goodwin, Terry Lyons, Kate E.A. Saunders
Identifying psychiatric diagnosis from missing mood data through the use of log-signature features
PLOS ONE, 2022

Talia Tseriotou, Adam Tsakalidis, Peter Foster, Terry Lyons, Maria Liakata
Sequential Path Signature Networks for Personalised Longitudinal Language Modeling
Findings of ACL, 2023

Cristopher Salvi, Joscha Diehl, Terry Lyons, Rosa Preiss, Jeremy Reizenstein
A structure theorem for streamed information
Journal of Algebra, 2023

Satoshi Hayakawa, Harald Oberhauser and Terry Lyons
Sampling-based Nystrom Approximation and Kernel Quadrature
Proceedings of the 40th International Conference on Machine Learning, 2023

Andy Wathen
Some comments on preconditioning for Normal Equations and Least Squares
2022, SIAM Review, vol. 64, lss. 3, pp. 640-649

Andy Wathen
Some observations on preconditioning for non-self-adjoint and time-dependent problems
2022, SIAM Journal on Matrix Analysis and Applications, vol. 116, pp. 176-180

Adeline Fermanian, Jiawei Chang, Terry Lyons and Gérard Biau
The insertion method to invert the signature of a path

Alexander Schell and Harald Oberhauser
Nonlinear Independent Component Analysis for Discrete-Time and Continuous-Time Signals
Accepted to appear in The Annals of Statistics   

Ben Walker, Felix Krones, Ivan Kiskin, Guy Parsons, Terry Lyons and Adam Mahdi
Dual Bayesian ResNet: A Deep Learning Approach to Heart Murmur Detection
2022 Computing in Cardiology (CinC), vol. 498, pp. 1-4

Carlos Améndola, Darrick Lee and Chiara Meroni
Convex Hulls of Curves: Volumes and Signatures

Congzheng Liu and Wenqi Zhu
Newsvendor Conditional Value-at-Risk Minimisation with a Non-Parametric Approach
Accepted for presentation at the 4th IMA and OR Society Conference on Mathematics of Operational Research, 2023

Cris Salvi, Adeline Fermanian, Terry Lyons and James Morrill
New directions in the applications of rough path theory
Accepted for publication in IEEE BITS the Information Theory Magazine

Karl Welzel and Raphael A Hauser
Generalizing Quasi-Newton Updates to Higher-Order Derivative Tensors

Michael B Giles
MLMC techniques for discontinuous functions
Accepted to appear in Proceedings of MCQMC 2022

Satoshi Hayakawa, Harald Oberhauser and Terry Lyons
Hypercontractivity meets Random Convex Hulls: Analysis of Randomized Multivariate Cubatures
Accepted for publication in Proceedings of the Royal Society A

Satoshi Hayakawa, Terry Lyons and Harald Oberhauser
Estimating the probability that a given vector is in the convex hull of a random sample
Probability Theory and Related Fields (2023)

Terry Lyons and Andrew D McLeod
Generalised Recombination Interpolation Method (GRIM)

Thomas Cass, Terry Lyons and Xingcheng Xu
Weighted signature kernels
Accepted for publication in Annals of Applied Probability

Vincent PH Goverse, Jad Hamdan and Jared Tanner
Optimal approximation complexity of high-dimensional functions with neural networks

Wenqi Zhu and Yuji Nakatsukasa
Convergence and Near-optimal Sampling for Multivariate Function Approximations in Irregular Domains via Vandermonde with Arnoldi
Accepted for presentation at the 29th Biennial Numerical Analysis Conference, 2023

Xiaoqi Xu, Darrick Lee, Nicolas Drougard and Raphaëlle N Roy
Signature methods for brain-computer interfaces

Scientific Reports, 2023

Zehong Zhang, Fei Lu, Esther Xu Fei, Terry Lyons, Yannis Kevrekidis and Tom Woolf
Benchmarking optimality of time series classification methods in distinguishing diffusions



Coralia Cartis and Zhen Shao
Random-subspace adaptive cubic regularisation method for nonconvex optimisationa>
Accepted paper for NeurIPS 2022 workshop "Order up! The Benefits of Higher-Order Optimization in Machine Learning”

Coralia Cartis, Jaroslav Fowkes and Zhen Shao
Randomised subspace methods for non-convex optimization, with applications to nonlinear least-squares arXiv:2211.09873

Csaba Toth, Darrick Lee, Celia Hacker and Harald Oberhauser
Capturing Graphs with Hypo-Elliptic Diffusions
Accepted to appear in Advances in Neural Information Processing Systems (NeurIPS 2022)

Elena Gal, Shaun Singh, Aldo Pacchiano, Ben Walker, Terry Lyons and Jakob Foerster
Unbiased decisions reduce regret: adversarial optimism for the bank loan problem

KeCheng Chen, Elena Gal, Hong Yan and Haoliang Li
Domain Generalization with small data

Masaki Adachi, Satoshi Hayakawa, Martin Jørgensen, Harald Oberhauser and Michael A Osborne
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination
Accepted to appear in Advances in Neural Information Processing Systems (NeurIPS 2022)

Mohamed R Ibrahim and Terry Lyons
ImageSig: A signature transform for ultra-lightweight image recognition
IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) 2022 

Oliver Sheridan-Methven and Michael Giles
Approximating inverse cumulative distribution functions to produce approximate random variables
Proceedings of International Congress on Mathematical Software 2024. To appear in the Springer series Lecture Notes in Computer Science (LNCS).

Patric Bonnier, Chong Liu and Harald Oberhauser
Adapted topologies and higher rank signatures
Accepted to appear in Annals of Applied Probability

Satoshi Hayakawa, Harald Oberhauser and Terry Lyons
Positively weighted kernel quadrature via subsampling
Accepted to appear in Advances in Neural Information Processing Systems (NeurIPS 2022)

Wenqi Zhu and Coralia Cartis
Quartic Polynomial Sub-problem Solutions in Tensor Methods for Nonconvex Optimization
Accepted paper for NeurIPS 2022 workshop "Order up! The Benefits of Higher-Order Optimization in Machine Learning”