Stein's method for marginals on large graphical models

arXiv:2410.11771 · stat.ML, cs.NA, math.NA · Submitted 2024-10-15 · Read on arXiv

stat.ML, cs.NA, math.NA

Submitted: 2024-10-15

Updated: 2026-08-31

Project page: https://chewisinho.github.io/main.pdf

Terminology

• Score Function — 16× in this paper · explained in 4 episodes
• Sample Complexity — 14× in this paper · explained in 15 episodes
• Inverse Problem — 10× in this paper · explained in 2 episodes
• Langevin Dynamics — 9× in this paper · explained in 2 episodes
• Wasserstein Distance — 8× in this paper · explained in 4 episodes
• Accuracy — 6× in this paper · explained in 1 episode
• Ambient Dimension — 4× in this paper · explained in 1 episode
• Curse of Dimensionality — 4× in this paper · explained in 6 episodes
• Sparsity — 4× in this paper · explained in 4 episodes
• Bayesian Inference — 3× in this paper · explained in 5 episodes
• Data Assimilation — 3× in this paper · explained in 2 episodes
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Diffusion Models — 2× in this paper · explained in 6 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• 2-Wasserstein Distance — 1× in this paper · explained in 1 episode
• Core — 1× in this paper · explained in 2 episodes
• Degeneracy — 1× in this paper · explained in 3 episodes
• Generative Modeling — 1× in this paper · explained in 3 episodes
• Generative Models — 1× in this paper · explained in 3 episodes
• Intrinsic Dimension — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Optimal Transport — 1× in this paper · explained in 5 episodes
• Variational Bayes — 1× in this paper · explained in 2 episodes

Sources

• Convergence of Unadjusted Langevin in High Dimensions: Delocalization of Bias
• Localized Diffusion Models
• Localized Schr\"odinger Bridge Sampler
• Transport Inequalities. A Survey
• Permutation Recovery on Manifold Data via Spectral Seriation
• Auto-Encoding Variational Bayes
• A hierarchical entropy method for the delocalization of bias in high-dimensional Langevin Monte Carlo

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