Control Variate Score Matching for Diffusion Models

arXiv:2512.20003 · cs.LG · Submitted 2025-12-23 · Read on arXiv

cs.LG

Submitted: 2025-12-23

Updated: 2026-09-01

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Diffusion Model — 8× in this paper · explained in 8 episodes
• Diffusion Models — 7× in this paper · explained in 6 episodes
• Target Score Identity — 7× in this paper
• Control Variate Score Identity — 6× in this paper
• Denoising Score Identity — 5× in this paper
• Gaussian Mixture Model — 5× in this paper
• Monte Carlo — 5× in this paper
• Gaussian Mixture Model (GMM) — 3× in this paper · explained in 2 episodes
• Negative Log-Likelihood — 3× in this paper
• Sample Complexity — 3× in this paper · explained in 15 episodes
• Diffusion Process — 2× in this paper · explained in 2 episodes
• 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
• Iterated Denoising Energy Matching — 2× in this paper
• Sample Efficiency — 2× in this paper · explained in 4 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• For the Target Score Matching — 1× in this paper
• Initial Data — 1× in this paper · explained in 2 episodes
• Score Function — 1× in this paper · explained in 4 episodes
• Selection Bias — 1× in this paper · explained in 4 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Target Score Matching
• Disentangling Total-Variance and Signal-to-Noise-Ratio Improves Diffusion Models

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