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score_sde_pytorch
PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)
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I was considering an unconditional latent diffusion model, but for conditional models, the computation becomes much more complex (we might have to use bayes here). If we use Score-Based Generative Modeling (https://arxiv.org/abs/2011.13456), we could try to find and count all the unique local minima and saddle points, but it is not clear how we can do this...
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