Diffusion Posterior Sampling (DPS)

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Key concept question for section 4?

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Option B

This is the correct answer because it captures the core concept.

Common Mistake: Common Mistake in Section 4

Mistake:

Overlooking a critical implementation detail.

Correction:

Always verify results against known benchmarks and theoretical predictions.

Key Term 4

Core concept from section 4 of chapter 43.

Theorem: PnP Fixed Point

PnP converges to a fixed point if the denoiser is firmly non-expansive: $\|D(\mathbf{x}) - D(\mathbf{y})\| \le \|\mathbf{x}-\mathbf{y}\|$ .

Theorem: DPS Posterior Sampling

DPS approximately samples from $p(\mathbf{x}|\mathbf{y})$ by modifying the reverse diffusion with a likelihood gradient step. The approximation error is $O(\alpha)$ where $\alpha$ is the step size.

Plug-and-Play (PnP) Reconstruction Self-Supervised Methods