Thibaut Germain

Thibaut Germain

Postdoctoral researcher in machine learning for dynamical systems at CMAP, Polytechnique, France.

Publications

You can also find my articles on my Google Scholar profile.

Journals papers

  1. Guerrini, V., Germain, T., Truong, C., Oudre, L, & Boniol, P. (2025). Time Series Motif Discovery: A Comprehensive Evaluation. Proceedings of the VLDB Endowment. [python package][github][pdf]
  2. Germain, T., Truong, C., & Oudre, L. (2024). Persistence-Based Motif Discovery in Time Series. IEEE Transactions on Knowledge and Data Engineering. [link][github][pdf]
  3. Germain, T., Truong, C., Oudre, L., & Krejci, E. (2023). Unsupervised classification of plethysmography signals with advanced visual representations. Frontiers in Physiology, 14, 1154328. [link][github][pdf]

International conferences papers

  1. Germain, T., Kosma, C., & Oudre, L. (2025). Time series representations with hard-coded invariances. In the 42nd International Conference on Machine Learning (ICML). [pdf]
  2. Germain, T., Gruffaz, S., Truong, C., Durmus, A., & Oudre, L. (2024). Shape analysis for time series. In 38th Annual Conference on Neural Information Processing Systems (NeurIPS). [link][github][pdf]
  3. Germain, T., Truong, C., & Oudre, L. (2024, August). Interactive motif discovery in time series with persistent homology. In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 383-387). Cham: Springer Nature Switzerland. [link][github][application][pdf]
  4. Germain, T., Truong, C., & Oudre, L. (2024, May). Linear-trend normalization for multivariate subsequence similarity search. In 2024 IEEE 40th International Conference on Data Engineering Workshops (ICDEW) (pp. 167-175). IEEE. [link][github][pdf]
  5. Germain, T., Truong, C., Oudre, L., & Krejci, E. (2022, July). Unsupervised study of plethysmography signals through DTW clustering. In 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC) (pp. 3396-3400). IEEE. [link][github][pdf]

Submited and preprint

  1. T. Germain, R. Flamary, V. R. Kostic, K. Lounici, A Spectral-Grassmann Wasserstein metric for operator representations of dynamical systems (Submited), 2025. [arXiv][pdf]

PhD Thesis

  1. Germain, T. “Pattern detection and shape analysis for physiological timeseries”. PhD thesis. Université Paris-Saclay, 2024. [pdf]

National conferences papers

  1. Germain, T., Bois, A. Truong, C., Tervil, B. & Oudre, L. (2023, September). Détection non supervisée de motifs sur séries temporelles. In Proceedings of the Groupe de Recherche et d’Etudes En Traitement Du Signal et Des Images (GRETSI), Grenoble, France, 2023. [link]
  2. Germain, T., Truong, C., Oudre, L., & Krejci, E. (2022, September). Approches non-supervisées et non-linéaires pour l’analyse de signaux de pléthysmographie. In Proceedings of the Groupe de Recherche et d’Etudes En Traitement Du Signal et Des Images (GRETSI), Nancy, France, 2022. [link]