44 citations · 137 across the 20 of their papers we have counts for
4 papers · 1 filter
Geodesic Sinkhorn for Fast and Accurate Optimal Transport on Manifolds
Guillaume Huguet, Alexander Tong, María Ramos Zapatero +3
Efficient computation of optimal transport distance between distributions is of growing importance in data science. Sinkhorn-based methods are currently the state-of-the-art for su…
Learnable Filters for Geometric Scattering Modules
Alexander Tong, Frederik Wenkel, Dhananjay Bhaskar +5
We propose a new graph neural network (GNN) module, based on relaxations of recently proposed geometric scattering transforms, which consist of a cascade of graph wavelet filters.…
Manifold Interpolating Optimal-Transport Flows for Trajectory Inference
Guillaume Huguet, D. S. Magruder, Alexander Tong +4
We present a method called Manifold Interpolating Optimal-Transport Flow (MIOFlow) that learns stochastic, continuous population dynamics from static snapshot samples taken at spor…
Time-inhomogeneous diffusion geometry and topology
Guillaume Huguet, Alexander Tong, Bastian Rieck +5
Diffusion condensation is a dynamic process that yields a sequence of multiscale data representations that aim to encode meaningful abstractions. It has proven effective for manifo…