Preprints and publications
Preprints and publications
2024
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)
2023
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
arXiv:2312.03523
Jason Rader, Terry Lyons, Patrick Kidger
Lineax: unified linear solves and linear least-squares in JAX and Equinox
arXiv:2311.17283
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
arXiv:2308.15336
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
APPLIED ENERGY, 2023
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
arXiv:2304.01862
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
arXiv:2301.09405
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
arXiv:2301.11678
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)
arXiv:2205.07495
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
arXiv:2301.13112
2022
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”
