Distribution Regression for Continuous-Time Processes via the Expected Signature. - Maud Lemercier; Cristopher Salvi; Theodoros Damoulas; Edwin V. Bonilla; Terry J. Lyons (CoRR, 2020)

Distribution Regression for Sequential Data. - Maud Lemercier; Cristopher Salvi; Theodoros Damoulas; Edwin V. Bonilla; Terry J. Lyons (AISTATS, 2021)

SK-Tree: a systematic malware detection algorithm on streaming trees via the signature kernel. - Thomas Cochrane; Peter Foster; Varun Chhabra; Maud Lemercier; Terry J. Lyons; Cristopher Salvi (CSR, 2021)

SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data. - Maud Lemercier; Cristopher Salvi; Thomas Cass; Edwin V. Bonilla; Theodoros Damoulas; Terry J. Lyons (ICML, 2021)

Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes. - Cristopher Salvi; Maud Lemercier; Chong Liu; Blanka Horvath; Theodoros Damoulas; Terry J. Lyons (NeurIPS, 2021)

Neural Stochastic Partial Differential Equations. - Cristopher Salvi; Maud Lemercier (CoRR, 2021)

Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics. - Cristopher Salvi; Maud Lemercier; Andris Gerasimovics (NeurIPS, 2022)

Learning on sequential data with evolution equations. - Maud Lemercier (2022)

Neural signature kernels as infinite-width-depth-limits of controlled ResNets. - Nicola Muca Cirone; Maud Lemercier; Cristopher Salvi (ICML, 2023)

Non-adversarial training of Neural SDEs with signature kernel scores. - Zacharia Issa; Blanka Horvath; Maud Lemercier; Cristopher Salvi (NeurIPS, 2023)

Novelty Detection on Radio Astronomy Data using Signatures. - Paola Arrubarrena; Maud Lemercier; Bojan Nikolic; Terry J. Lyons; Thomas Cass (CoRR, 2024)

A High Order Solver for Signature Kernels. - Maud Lemercier; Terry J. Lyons (CoRR, 2024)