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Spectral Diffusion Processes

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arxiv 2209.14125 v2 pith:4BJ2YVKZ submitted 2022-09-28 stat.ML cs.LG

Spectral Diffusion Processes

Angus Phillips , Thomas Seror , Michael Hutchinson , Valentin De Bortoli , Arnaud Doucet , Emile Mathieu This is my paper
classification stat.ML cs.LG
keywords modellingfunctionalgenerativemethodpartprocessesspacesspectral
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Score-based generative modelling (SGM) has proven to be a very effective method for modelling densities on finite-dimensional spaces. In this work we propose to extend this methodology to learn generative models over functional spaces. To do so, we represent functional data in spectral space to dissociate the stochastic part of the processes from their space-time part. Using dimensionality reduction techniques we then sample from their stochastic component using finite dimensional SGM. We demonstrate our method's effectiveness for modelling various multimodal datasets.

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Cited by 4 Pith papers

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