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.
Highly accurate protein structure prediction with alphafold.nature, 596(7873):583– 589, 2021
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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.