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Maud Lemercier

I am a PhD student at the University of Warwick, and a visiting researcher at the Alan Turing Institute, working under the supervision of Prof. Theo Damoulas. I am part of the Oxford-Warwick CDT programme (OxWaSP). I am also a member of the Warwick Machine Learning Group and the DataSig team. My research focuses on developing methodologies, leveraging tools from rough path theory, to perform inference on large and complex datasets of multivariate sequential data.

Prior to joining OxWaSP, I completed an MSc in Machine Learning at Imperial College London, and obtained a Degree of Engineering at IMT Atlantique, in France.

I co-organise the Warwick Machine Learning Reading Group.

Publications & Preprints

C. Salvi, M. Lemercier & A. Gerasimovics. Neural Stochastic Partial Differential Equations. (arXiv)

C. Salvi, M. Lemercier, C. Liu, B. Hovarth, T. Damoulas & T. Lyons. Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes. In Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021).

M. Lemercier, C. Salvi, T. Cass, E. V. Bonilla, T. Damoulas & T. Lyons. SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data. In International Conference on Machine Learning (ICML 2021).

T. Cochrane, P. Foster, V. Chhabra, M. Lemercier, C. Salvi & T. Lyons. SK-Tree: a systematic malware detection algorithm on streaming trees via the signature kernel. In IEEE International Conference on Cyber Security and Resilience (IEEE CSR 2021).

M. Lemercier, C. Salvi, T. Damoulas, E. V. Bonilla & T. Lyons. Distribution Regression for Sequential Data. In International Conference on Artificial Intelligence and Statistics (AISTATS 2021).

Talks & Posters

Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes, NeurIPS MeetUp Cambridge, University of Cambridge (December 2021)

Distribution Regression on Sequential Data, ICERM Workshop in partnership with DataSig, Brown University (July 2021, Remote)

Higher Order Mean Embeddings for Stochastic Processes, Data‑Centric Engineering Reading Group, Alan Turing Institute (June 2021, Remote)

Higher Order Mean Embeddings for Stochastic Processes, Young Researchers' Meeting, University of Warwick (June 2021, Remote)

Inference from Evolving Populations: Agriculture, Unlocking Data Streams Workshop, Newton Gateway to Mathematics (March 2021, Remote)

Scaling Gaussian Process Inference on Sequential Data, Data Science Theme Meeting, University of Warwick (February 2021, Remote)

Distribution Regression for Continuous-Time Processes via the Expected Signature, Data‑Centric Engineering Reading Group, Alan Turing Institute (July 2020, Remote)