Publications & Preprint
- M. Carrière, M. Theveneau, TL. Diffeomorphic interpolation for efficient persistence-based topological optimization. preprint.
- Y. Hiraoka, Y. Imoto, K. Meehan, TL, T. Yachimura Topological Node2vec: Enhanced Graph Embedding via Persistent Homology. Journal of Machine Learning Research.
- T. Dumont, TL, FX. Vialard On The Existence Of Monge Maps For The Gromov-Wasserstein Problem. Foundation of Computational Mathematics, 2024.
- F. Hensel, C. Arnal, M. Carrière, TL, H. Kurihara, Y. Ike, F. Chazal, MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks, TMLR.
- T. de Surrel, F. Hensel, M. Carrière, TL, M. Glisse, H. Kurihara, Y. Ike and F. Chazal. RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. ICLR, Topological, Algebraic and Geometric Learning workshop, 2022.
- TL. An Homogeneous Unbalanced Regularized Optimal Transport model with applications to Optimal Transport with Boundary, AISTATS 2023. Code.
- J.Leygonie, M.Carrière, TL, S.Oudot. A Gradient Sampling Algorithm for Stratified Maps with Applications to Topological Data Analysis, Mathematical Programming.
- V. Divol, TL. Estimation and Quantization of Expected Persistence Diagrams, ICML 2021.
- TL, Y. Ike, M. Carriere, F. Chazal, M. Glisse, Y. Umeda. Topological Uncertainty: Monitoring Trained Neural Networks Through Persistence of Activation Graphs, IJCAI 2021.
- M. Carriere, F. Chazal, Y. Ike, TL, M. Royer, Y. Umeda. PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures, AISTATS 2020.
- V. Divol, TL. Understanding the Topology and the Geometry of the Space of Persistence via Optimal Partial Transport, Journal of Applied and Computational Topology.
- TL, M. Cuturi, S. Oudot. Large Scale Computation of Means and Cluster for Persistence Diagrams using Optimal Transport, NeurIPS 2018.
Software
I contribute to the Python API of the GUDHI library, where I release tools to deal with persistence diagrams (PDs) using Optimal Transport based on algorithms developed by the OT community, adapted to PDs.
Supervision
Ph.D. students
- (Sept 2023-) Théo Dumont, Ph.D. Co-supervised with François-Xavier Vialard and Virginie Ehrlacher.
Interns
- (2022) Maxime Guigon, École polytechnique, master internship.
- (2022) Théo Dumont, École des Mines de Paris, master internship.
- (2023) Marc Theveneau, École polytechnique, master internship.
- (2024) Tung Nguyen, Université Gustave Eiffel (Labex Bézout), master internship.
Material
- I wrote a TDA tutorial. An html preview is available here, and you can download a zip archive here. This material was produced for the AMS-MRC week I am co-organizing.
- My Ph.D. thesis manuscript can be found here. You can find the corresponding slides there, and a video recording of the defense itself there.
Reviewer activity in conferences and journals