Research map / Probabilistic and scientific modeling / Variational and generative sampling
Statistical Efficiency of Score Matching: The View from Isoperimetry
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add a sufficient statistic encoding the sparse cut between modes | Score matching in the bimodal exponential-family experiment · Bimodal distribution | fit quality relative to MLE | Hurt |
| Remove the sufficient statistic correlated with the sparse cut (ablation) | Score matching in the bimodal exponential-family experiment · Bimodal distribution | fit quality relative to MLE | Helped |
| Increase the oscillation frequency of the sufficient statistic | Score matching · Unimodal distribution with rapidly oscillating sufficient statistic | parameter-estimation accuracy relative to MLE | Hurt |
| Increase the separation between Gaussian mixture modes | Score matching with a one-hidden-layer tanh network · Mixture of two Gaussians | distribution fit quality | Hurt |
Closest papers by meaning
- Provable benefits of score matching (NeurIPS 2023 · similarity 0.89)
- Dimension-free Score Matching and Time Bootstrapping for Diffusion Models (NeurIPS 2025 · similarity 0.87)
- Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization (ICLR 2024 · similarity 0.87)
- Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance (ICML 2025 · similarity 0.86)
- Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization (ICLR 2024 · similarity 0.86)
- Score Matching with Missing Data (ICML 2025 · similarity 0.86)
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