11 citations · 33 across the 12 of their papers we have counts for
4 papers · 1 filter
Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics
Cristopher Salvi, Maud Lemercier, Andris Gerasimovics
Stochastic partial differential equations (SPDEs) are the mathematical tool of choice for modelling spatiotemporal PDE-dynamics under the influence of randomness. Based on the noti…
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…