Théo Lacombe - RankMe

24 papers A* 4A 2Journal 16Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Persistence-based topological optimization: a survey. CoRR Mathieu Carrière, Yuichi Ike, Théo Lacombe, Naoki Nishikawa
2026	J	`jnl`	Revisiting the Sliced Wasserstein Kernel for persistence diagrams: a Figalli-Gigli approach. CoRR Marc Janthial, Théo Lacombe
2025	J	`jnl`	On the Existence of Monge Maps for the Gromov-Wasserstein Problem. Found. Comput. Math. Théo Dumont, Théo Lacombe, François-Xavier Vialard
2024	A*	`conf`	Diffeomorphic interpolation for efficient persistence-based topological optimization. NeurIPS Mathieu Carrière, Marc Theveneau, Théo Lacombe
2024	J	`jnl`	Diffeomorphic interpolation for efficient persistence-based topological optimization. CoRR Mathieu Carrière, Marc Theveneau, Théo Lacombe
2024	J	`jnl`	MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Neural Networks. Trans. Mach. Learn. Res. Charles Arnal, Felix Hensel, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
2024	J	`jnl`	Topological Node2vec: Enhanced Graph Embedding via Persistent Homology. J. Mach. Learn. Res. Yasuaki Hiraoka, Yusuke Imoto, Théo Lacombe, Killian Meehan, Toshiaki Yachimura
2023	J	`jnl`	A gradient sampling algorithm for stratified maps with applications to topological data analysis. Math. Program. Jacob Leygonie, Mathieu Carrière, Théo Lacombe, Steve Oudot
2023	A	`conf`	An Homogeneous Unbalanced Regularized Optimal Transport Model with Applications to Optimal Transport with Boundary. AISTATS Théo Lacombe
2023	J	`jnl`	MAGDiff: Covariate Data Set Shift Detection via Activation Graphs of Deep Neural Networks. CoRR Felix Hensel, Charles Arnal, Mathieu Carrière, Théo Lacombe, Hiroaki Kurihara, Yuichi Ike, Frédéric Chazal
2023	J	`jnl`	Topological Node2vec: Enhanced Graph Embedding via Persistent Homology. CoRR Yasuaki Hiraoka, Yusuke Imoto, Killian Meehan, Théo Lacombe, Toshiaki Yachimura
2022	—	`conf`	RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. TAG-ML Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
2022	J	`jnl`	RipsNet: a general architecture for fast and robust estimation of the persistent homology of point clouds. CoRR Thibault de Surrel, Felix Hensel, Mathieu Carrière, Théo Lacombe, Yuichi Ike, Hiroaki Kurihara, Marc Glisse, Frédéric Chazal
2021	J	`jnl`	A Gradient Sampling Algorithm for Stratified Maps with Applications to Topological Data Analysis. CoRR Jacob Leygonie, Mathieu Carrière, Théo Lacombe, Steve Oudot
2021	A*	`conf`	Estimation and Quantization of Expected Persistence Diagrams. ICML Vincent Divol, Théo Lacombe
2021	A*	`conf`	Topological Uncertainty: Monitoring Trained Neural Networks through Persistence of Activation Graphs. IJCAI Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
2021	J	`jnl`	Topological Uncertainty: Monitoring trained neural networks through persistence of activation graphs. CoRR Théo Lacombe, Yuichi Ike, Mathieu Carrière, Frédéric Chazal, Marc Glisse, Yuhei Umeda
2021	J	`jnl`	Understanding the topology and the geometry of the space of persistence diagrams via optimal partial transport. J. Appl. Comput. Topol. Vincent Divol, Théo Lacombe
2020	A	`conf`	PersLay: A Neural Network Layer for Persistence Diagrams and New Graph Topological Signatures. AISTATS Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
2020	—	`—`	Statistics for Topological Descriptors using optimal transport. (Statistiques sur les descripteurs topologiques à base de transport optimal). Théo Lacombe
2019	J	`jnl`	A General Neural Network Architecture for Persistence Diagrams and Graph Classification. CoRR Mathieu Carrière, Frédéric Chazal, Yuichi Ike, Théo Lacombe, Martin Royer, Yuhei Umeda
2019	J	`jnl`	Understanding the Topology and the Geometry of the Persistence Diagram Space via Optimal Partial Transport. CoRR Vincent Divol, Théo Lacombe
2018	A*	`conf`	Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport. NeurIPS Théo Lacombe, Marco Cuturi, Steve Oudot
2018	J	`jnl`	Large Scale computation of Means and Clusters for Persistence Diagrams using Optimal Transport. CoRR Théo Lacombe, Marco Cuturi, Steve Oudot