Research

Since October 2020, I am doing a PhD on geometric manifold learning under the supervision of Xavier Pennec and Alain Trouvé. More specifically, my thesis focuses on designing intrinsic methods for the analysis of manifold-valued data with a particular interest for shape data and graph data. I leverage Riemannian models and explore non-metric structures such as barycentric subspaces. Additionally, I look for approximations by constant curvature spaces.

Papers

• Nina Miolane, et al. ICLR 2021 challenge for computational geometry & topology: Design and results. arXiv:2108.09810.

• Nicolas Guigui, Elodie Maignant, Alain Trouvé, Xavier Pennec. Parallel Transport on Kendall Shape Spaces. Geometric Science of Information: 5th International Conference, GSI’21. Springer International Publishing (2021). arXiv:2103.04611

• Maxim Stolyarchuk, Julie Ledoux, Elodie Maignant, Alain Trouvé, Luba Tchertanov Identification of the Primary Factors Determining the Specificity of the human VKORC1 Recognition by Thioredoxin-fold Proteins. International Journal of Molecular Sciences 22.2 (2021): 802. hal-03042382

• Philipp Harms, Elodie Maignant, Stefan Schlager. Approximation of Riemannian Distances and Applications to Distance-Based Learning on Manifolds. arXiv:1904.11860.

• Philipp Harms, Elodie Maignant. Approximations of distances and kernels on shape space. Math in the Black Forest – Workshop on New Directions in Shape Analysis (2018). arXiv:1811.01370.

Talks

• April 2023 – Working with unlabelled graphs. Epione PhD Seminar. Inria, France.

• October 2022 – Some keys to understand Laplacian eigenmaps. Epione PhD Seminar Inria, France.

• September 2022 – Looking for invariance in Locally Linear Embedding (Poster). Research School on Geometry and Statistics in Data Sciences Cargese, France.

• June 2022 – Looking for invariance in Locally Linear Embedding (Poster). 10th International Conference on Curves and Surfaces. Arcachon, France.

• March 2022 – Understanding Geodesic PCA on a simple application. Epione PhD Seminar. Inria, France

• January 2022 – Introducing a generalisation of Locally Linear Embedding to manifold-valued data. Groupement de Travail en Traitement d’Images. ENS Paris-Saclay, France.

• November 2021 – A generalisation of Locally Linear Embedding to manifold-valued data. PhD Seminar in Analysis, LMO. Université Paris-Saclay (Orsay), France.

• October 2021 – A generalisation of Locally Linear Embedding to manifold-valued data. Congrès des Jeunes Chercheuses et Chercheurs en Mathématiques Appliquées. École Polytechnique, France.

• September 2021 – A gentle introduction to parallel transport and shape analysis. Epione PhD Seminar. Inria, France.

• August 2021 – Visualisation of Kendall shape spaces with Geomstats. Graduate Student Conference on Geometry and Topology meet Data Analysis and Machine Learning..

• July 2021 – Parallel transport on Kendall shape spaces. 5th International Conference on Geometric Science of Information. Paris, France