research
∙
07/05/2023
Implicit Differentiation for Hyperparameter Tuning the Weighted Graphical Lasso
We provide a framework and algorithm for tuning the hyperparameters of t...
share
research
∙
05/23/2023
SNEkhorn: Dimension Reduction with Symmetric Entropic Affinities
Many approaches in machine learning rely on a weighted graph to encode t...
research
∙
03/09/2023
Entropic Wasserstein Component Analysis
Dimension reduction (DR) methods provide systematic approaches for analy...
research
∙
10/21/2022
Learning Graphical Factor Models with Riemannian Optimization
Graphical models and factor analysis are well-established tools in multi...
research
∙
05/31/2022
Template based Graph Neural Network with Optimal Transport Distances
Current Graph Neural Networks (GNN) architectures generally rely on two ...
research
∙
12/01/2021
Controlling Wasserstein distances by Kernel norms with application to Compressive Statistical Learning
Comparing probability distributions is at the crux of many machine learn...
research
∙
10/06/2021
Semi-relaxed Gromov Wasserstein divergence with applications on graphs
Comparing structured objects such as graphs is a fundamental operation i...
research
∙
04/29/2021
Fast Multiscale Diffusion on Graphs
Diffusing a graph signal at multiple scales requires computing the actio...
research
∙
02/12/2021
Online Graph Dictionary Learning
Dictionary learning is a key tool for representation learning, that expl...
research
∙
11/09/2020
A contribution to Optimal Transport on incomparable spaces
Optimal Transport is a theory that allows to define geometrical notions ...
research
∙
02/10/2020
Time Series Alignment with Global Invariances
In this work we address the problem of comparing time series while takin...
research
∙
02/10/2020
CO-Optimal Transport
Optimal transport (OT) is a powerful geometric and probabilistic tool fo...
research
∙
05/24/2019
Sliced Gromov-Wasserstein
Recently used in various machine learning contexts, the Gromov-Wasserste...
research
∙
11/07/2018
Fused Gromov-Wasserstein distance for structured objects: theoretical foundations and mathematical properties
Optimal transport theory has recently found many applications in machine...
research
∙
05/23/2018
