Kinetic Langevin Meets Split Gibbs: Accelerated Posterior Sampling for Imaging Inverse Problems with Diffusion Priors

arXiv:2610.10187 · stat.ML, cs.LG · Submitted 2026-10-07 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-10-07

Updated: 2026-10-07

Terminology

• Split Gibbs Sampling — 17× in this paper
• Regularization — 10× in this paper · explained in 3 episodes
• Diffusion Model — 8× in this paper · explained in 8 episodes
• Diffusion Models — 8× in this paper · explained in 6 episodes
• Inverse Problem — 8× in this paper · explained in 2 episodes
• Fidelity — 5× in this paper · explained in 2 episodes
• Generative Model — 4× in this paper · explained in 2 episodes
• Image Restoration — 4× in this paper
• Gradient Flow — 3× in this paper · explained in 2 episodes
• Bayesian Inference — 2× in this paper · explained in 5 episodes
• Data Augmentation — 2× in this paper · explained in 7 episodes
• Homogeneity — 2× in this paper · explained in 2 episodes
• Langevin Monte Carlo — 2× in this paper
• Theoretical Guarantees — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Convergence Guarantees — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative Models — 1× in this paper · explained in 3 episodes
• Hyperparameters — 1× in this paper · explained in 2 episodes
• Langevin Dynamics — 1× in this paper · explained in 2 episodes
• Non-asymptotic Analysis — 1× in this paper · explained in 2 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes
• Wasserstein Distance — 1× in this paper · explained in 4 episodes

Sources

• ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models
• Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference
• Multiple Wasserstein Gradient Descent Algorithm for Multi-Objective Distributional Optimization
• Accelerated Multiple Wasserstein Gradient Flows for Multi-objective Distributional Optimization

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