A generative sampling method that runs a full-order stochastic differential equation in a Double Diffusion Maps latent space and lifts samples back to the data space via Geometric Harmonics.
Learning particle physics by example: location-aware generative adversarial networks for physics synthesis.Computing and Software for Big Science, 1(1):4, 2017
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Enabling Probabilistic Learning on Manifolds through Double Diffusion Maps
A generative sampling method that runs a full-order stochastic differential equation in a Double Diffusion Maps latent space and lifts samples back to the data space via Geometric Harmonics.