|
Diana Marin, Amal Dev Parakkat, Stefan Ohrhallinger, Michael Wimmer, Steve Oudot and Pooran Memari. SING: Stability-Incorporated Neighborhood Graph. SIGGRAPH Asia 2024 Conference Papers, article 130, 2024.
|
|
|
Luis Scoccola, Siddharth Setlur, David Loiseaux, Mathieu Carrière and Steve Oudot. Differentiability and Optimization of Multiparameter Persistent Homology. Proc. 41st International Conference on Machine Learning (ICML), 2024.
|
|
|
Soham Mukherjee, Shreyas N. Samaga, Cheng Xin, Steve Oudot and Tamal K. Dey. D-GRIL: End-to-End Topological Learning with 2-parameter Persistence. ArXiv preprint 2406.07100 [LG], June 2024.
|
|
|
David Loiseaux, Luis Scoccola, Mathieu Carrière, Magnus Botnan and Steve Oudot. Stable Vectorization of Multiparameter Persistent Homology using Signed Barcodes as Measures. Proc. 37th Conference on Neural Information Processing Systems (NeurIPS), 2023.
|
|
|
Jacob Leygonie, Mathieu Carrière, Théo Lacombe and Steve Oudot. A Gradient Sampling Algorithm for Stratified Maps with Applications to Topological Data Analysis. Mathematical Programming, 202:199--239, 2023.
|
|
|
Rachel Jeitziner, Mathieu Carrière, Jacques Rougemont, Steve Oudot, Kathryn Hess, and Cathrin Brisken.
Two-Tier Mapper: a user-independent clustering method for global gene expression analysis based on topology. Bioinformatics, Oxford University Press, Feb. 2019.
|
|
|
Théo Lacombe, Marco Cuturi and Steve Y. Oudot.
Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport. Proc. 32nd Conference on Neural Information Processing Systems (NIPS), 2018.
|
|
|
Mathieu Carrière, Bertrand Michel and Steve Y. Oudot.
Statistical Analysis and Parameter Selection for Mapper.
Journal of Machine Learning Research, 19(12):1-39, 2018.
|
|
|
Thomas Bonis and Steve Y. Oudot.
A fuzzy clustering algorithm for the mode-seeking framework. Pattern Recognition Letters, 102:37-43, 2018.
|
|
|
Mathieu Carrière, Marco Cuturi and Steve Oudot.
Sliced Wasserstein Kernel for Persistence Diagrams.
Proc. 34th International Conference on Machine Learning (ICML), 2017.
|
|
|
Thomas Bonis, Frédéric Chazal, Steve Oudot and Maksim Ovsjanikov. Persistence-based Pooling for Shape
Pose Recognition. Proc. 6th International Workshop on
Computational Topology in Image Context (CTIC), June 2016,
Marseille.
|
|
|
Mathieu Carrière, Steve Y. Oudot, and Maksim Ovsjanikov. Stable
Topological Signatures for Points on 3D Shapes. Proc. Sympos. on
Geometry Processing, July 2015.
|
|
|
Mickaël Buchet, Frédéric Chazal, Tamal K. Dey,
Fengtao Fan,
Steve Y. Oudot, and Yusu Wang. Topological analysis of scalar fields
with outliers. Proc. Sympos. on Computational Geometry,
June 2015.
|
 |
|
M. Buchet and F. Chazal and S. Y. Oudot and D. R. Sheehy. Efficient
and Robust Topological Data Analysis on Metric Spaces. Proc. ACM-SIAM
Symposium on Discrete Algorithms (SODA), January 2015.
|
 |
|
F. Chazal,
L. J. Guibas, S. Y. Oudot, P. Skraba. Persistence-Based
Clustering in Riemannian Manifolds. Journal of the ACM, volume 60,
issue 6, article 41, 2013. A short version appeared in Proc. 27th Annual ACM
Symposium on Computational Geometry, 2011.
|
|
|
B. Hudson, G. L. Miller, S. Y. Oudot, D. R. Sheehy. Topological
Inference via Meshing. Proc. 26th Annual ACM Symposium
on Computational Geometry, pages 277-286, 2010.
|
 |
|
F. Chazal,
D. Cohen-Steiner, L. J. Guibas, F. Mémoli,
S. Y. Oudot. Gromov-Hausdorff Stable Signatures for Shapes using
Persistence. Computer Graphics Forum (proc. SGP 2009),
pages 1393-1403.
|
 |
|
F. Chazal,
L. J. Guibas, S. Y. Oudot, P. Skraba. Analysis of Scalar Fields over
Point Cloud Data. Proc. 19th ACM-SIAM Symposium on Discrete
Algorithms, pp. 1021-1030, 2009. Full version in Discrete
and Computational Geometry (DCG), 46(4):743--775, December 2011 (full version).
|
 |
|
F. Chazal, S. Y. Oudot. Towards Persistence-Based Reconstruction in Euclidean Spaces. Proc. 24th ACM Sympos. on Comput. Geom., pages 232-241, 2008 (full version).
|
 |
|