7 citations · 7 across the 1 of their papers we have counts for
5 papers
Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes
Cristopher Salvi, Maud Lemercier, Chong Liu +3
Stochastic processes are random variables with values in some space of paths. However, reducing a stochastic process to a path-valued random variable ignores its filtration, i.e. t…
SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data
Maud Lemercier, Cristopher Salvi, Thomas Cass +3
Making predictions and quantifying their uncertainty when the input data is sequential is a fundamental learning challenge, recently attracting increasing attention. We develop Sig…
SK-Tree: a systematic malware detection algorithm on streaming trees via the signature kernel
Thomas Cochrane, Peter Foster, Varun Chhabra +3
The development of machine learning algorithms in the cyber security domain has been impeded by the complex, hierarchical, sequential and multimodal nature of the data involved. In…
Sig-SDEs model for quantitative finance
Imanol Perez Arribas, Cristopher Salvi, Lukasz Szpruch
Mathematical models, calibrated to data, have become ubiquitous to make key decision processes in modern quantitative finance. In this work, we propose a novel framework for data-d…
Deep Signature Transforms
Patric Bonnier, Patrick Kidger, Imanol Perez Arribas +2
The signature is an infinite graded sequence of statistics known to characterise a stream of data up to a negligible equivalence class. It is a transform which has previously been…