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Found 6 papers, 2 papers with code
Manifold Interpolating Optimal-Transport Flows for Trajectory Inference
In GAE the latent space distance between points is regularized to match a novel multiscale geodesic distance on the data manifold that we define.
Time-inhomogeneous diffusion geometry and topology
From a geometric perspective, we obtain convergence bounds based on the smallest transition probability and the radius of the data, whereas from a spectral perspective, our bounds are based on the eigenspectrum of the diffusion kernel.
Embedding Signals on Knowledge Graphs with Unbalanced Diffusion Earth Mover's Distance
We propose to compare and organize such datasets of graph signals by using an earth mover's distance (EMD) with a geodesic cost over the underlying graph.
Diffusion Earth Mover's Distance and Distribution Embeddings
Here, Diffusion EMD can derive distances between patients on the manifold of cells at least two orders of magnitude faster than equally accurate methods.
Multimodal Data Visualization and Denoising with Integrated Diffusion
We propose a method called integrated diffusion for combining multimodal datasets, or data gathered via several different measurements on the same system, to create a joint data diffusion operator.
Coarse Graining of Data via Inhomogeneous Diffusion Condensation
Here, we consider multiple levels of abstraction via a multiresolution geometry of data points at different granularities.
