Maud Lemercier

According to our database1, Maud Lemercier authored at least 13 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

On csauthors.net:

Bibliography

2025
Novelty detection on path space.
CoRR, December, 2025

2024
A High Order Solver for Signature Kernels.
CoRR, 2024

Novelty Detection on Radio Astronomy Data using Signatures.
CoRR, 2024

2023
Non-adversarial training of Neural SDEs with signature kernel scores.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Neural signature kernels as infinite-width-depth-limits of controlled ResNets.
Proceedings of the International Conference on Machine Learning, 2023

2022
Learning on sequential data with evolution equations.
PhD thesis, 2022

Neural Stochastic PDEs: Resolution-Invariant Learning of Continuous Spatiotemporal Dynamics.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
Neural Stochastic Partial Differential Equations.
CoRR, 2021

Higher Order Kernel Mean Embeddings to Capture Filtrations of Stochastic Processes.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

SigGPDE: Scaling Sparse Gaussian Processes on Sequential Data.
Proceedings of the 38th International Conference on Machine Learning, 2021

SK-Tree: a systematic malware detection algorithm on streaming trees via the signature kernel.
Proceedings of the IEEE International Conference on Cyber Security and Resilience, 2021

Distribution Regression for Sequential Data.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020
Distribution Regression for Continuous-Time Processes via the Expected Signature.
CoRR, 2020


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