Robust Bayesian Inference for Unnormalized Models with Mixed-Domain Data

arXiv:2609.01783 · stat.ME, stat.ML · Submitted 2026-09-01 · Read on arXiv

stat.ME, stat.ML

Submitted: 2026-09-01

Updated: 2026-09-16

Terminology

• Bayesian Inference — 21× in this paper · explained in 5 episodes
• Consistency — 8× in this paper · explained in 3 episodes
• Uncertainty Quantification — 7× in this paper · explained in 8 episodes
• Calibration — 6× in this paper · explained in 7 episodes
• Robustness — 6× in this paper · explained in 5 episodes
• Score Function — 6× in this paper · explained in 4 episodes
• Bayesian Framework — 3× in this paper · explained in 3 episodes
• Core — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Modeling — 2× in this paper · explained in 3 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Objective Function — 2× in this paper · explained in 2 episodes
• Bernstein-von Mises — 1× in this paper
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Empirical Coverage — 1× in this paper · explained in 2 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Hilbert Space — 1× in this paper · explained in 2 episodes
• Modularity — 1× in this paper · explained in 9 episodes
• Simulation-based Inference — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Amortised and provably-robust simulation-based inference
• Marked spatial point processes: current state and extensions to point processes on linear networks
• Regularized Exponentially Tilted Empirical Likelihood for Bayesian Inference
• Statistical Efficiency of Score Matching: The View from Isoperimetry
• The Principles of Diffusion Models
• Interpretation and Generalization of Score Matching
• Score matching estimators for directional distributions
• MCMC for doubly-intractable distributions
• A Unified Measure-Theoretic View of Diffusion, Score-Based, and Flow Matching Generative Models
• Contrastive Bayesian Inference for Unnormalized Models

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