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Conditional Simulation Using Diffusion Schrödinger Bridges
[article]
2022
arXiv
pre-print
Denoising diffusion models have recently emerged as a powerful class of generative models. They provide state-of-the-art results, not only for unconditional simulation, but also when used to solve conditional simulation problems arising in a wide range of inverse problems. A limitation of these models is that they are computationally intensive at generation time as they require simulating a diffusion process over a long time horizon. When performing unconditional simulation, a Schr\"odinger
arXiv:2202.13460v2
fatcat:c2tlq7f72ff6lfn4uz4qanakzq