26 citations · 26 across the 4 of their papers we have counts for
9 papers
Differentiable latent structure discovery for interpretable forecasting in clinical time series
Ivan Lerner, Jean Feydy, Alexandre Kalimouttou +2
Background: We introduce StructGP, a continuous-time multi-task Gaussian process that couples process convolutions with differentiable structure learning to uncover a sparse, order…
Gromov-Wasserstein at Scale, Beyond Squared Norms
Guillaume Houry, Jean Feydy, François-Xavier Vialard
A fundamental challenge in data science is to match disparate point sets with each other. While optimal transport efficiently minimizes point displacements under a bijectivity cons…
Untangling Vascular Trees for Surgery and Interventional Radiology
Guillaume Houry, Tom Boeken, Stéphanie Allassonnière +1
The diffusion of minimally invasive, endovascular interventions motivates the development of visualization methods for complex vascular networks. We propose a planar representation…
Sinkhorn Normalization of Diffusion Kernels
Nathan Kessler, Robin Magnet, Jean Feydy
Smoothing a signal based on local neighborhoods is a core operation in machine learning and geometry processing. On well-structured domains such as vector spaces and manifolds, the…
Fast Large Deformation Matching with the Energy Distance Kernel
Siwan Boufadene, François-Xavier Vialard, Jean Feydy
We propose an efficient framework for point cloud and measure registration using bi-Lipschitz homeomorphisms, achieving O(n log n) complexity, where n is the number of points. By l…
Accurate Point Cloud Registration with Robust Optimal Transport
Zhengyang Shen, Jean Feydy, Peirong Liu +4
This work investigates the use of robust optimal transport (OT) for shape matching. Specifically, we show that recent OT solvers improve both optimization-based and deep learning m…