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Showing 1 to 2 of 2 for “"Normalising flows"”.

  1. Advancing Normalising Flows to Model Boltzmann Distributions

    … serve as a surrogate. Popular for this task are normalising flows, which are tractable density models. This thesis is focused on ameliorating methods to implement, sample from, and train normalising flows as well as enhance their architecture with emphasis on the application to Boltzmann …

    cambridge Repository record for Advancing Normalising Flows to Model Boltzmann Distributions (opens in a new tab)

  2. Towards Learning the Geometry of Data: From Diffusion Models to Riemannian Geometry

    … In chapter 3, we introduce CAFLOW, a conditional normalising flow that improves image-to-image translation by hierarchically modelling image distributions across scales. In chapter 4, we introduce non-uniform diffusion models, which apply faster diffusion speed to high-frequency information and …

    cambridge Repository record for Towards Learning the Geometry of Data: From Diffusion Models to Riemannian Geometry (opens in a new tab)