PnP-CM treats consistency models as plug-and-play priors inside an ADMM solver with noise perturbations and momentum updates to solve linear and nonlinear inverse problems in as few as 2-4 neural function evaluations.
Simplifying, stabilizing and scaling continuous-time consistency models
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PnP-CM: Consistency Models as Plug-and-Play Priors for Inverse Problems
PnP-CM treats consistency models as plug-and-play priors inside an ADMM solver with noise perturbations and momentum updates to solve linear and nonlinear inverse problems in as few as 2-4 neural function evaluations.