Preprints and publications

Preprints and publications

2023


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


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
arXiv:2012.09715


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”