"Example-Based Sampling with Diffusion Models. (arXiv:2302.05116v1 [cs.GR])" — A generic way to produce 2-d point sets imitating existing samplers from observed point sets using a diffusion model which addresses the problem of convolutional layers by leveraging neighborhood information from an optimal transport matching to a uniform grid, that allows benefiting from fast convolutions on grids, and to support the example-based learning of non-uniform sampling patterns.

Paper: http://arxiv.org/abs/2302.05116

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