DIPA learns preconditioning operators via distillation from a teacher with a better sensing matrix to improve reconstruction quality for the student's physically constrained matrix in imaging inverse problems.
Image restoration by denoising diffusion models with iteratively preconditioned guidance, in: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp
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DIPA: Distilled Preconditioned Algorithms for Solving Imaging Inverse Problems
DIPA learns preconditioning operators via distillation from a teacher with a better sensing matrix to improve reconstruction quality for the student's physically constrained matrix in imaging inverse problems.