Research map / Probabilistic and scientific modeling / Variational and generative sampling
Generalized Precision Matrix for Scalable Estimation of Nonparametric Markov Networks
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use regularized score matching with the GPM estimator instead of KCI | Markov network structure learning · 12 variables | running time: 247 s vs 62.9 s | Helped |
| Use regularized score matching with the GPM estimator instead of GS | Markov network structure learning · 12 variables | running time: 9536.5 s vs 62.9 s | Helped |
| Use regularized score matching with the GPM estimator instead of SING | Continuous Markov network structure learning · 12 variables | running time: 4020.3 s vs 62.9 s | Helped |
| Use the GPM method rather than GLASSO or NPN | Markov network structure learning on general distributions · Distributions from random graphs | Hamming distance | Mixed |
| Use the GPM method on more complex random-graph distributions rather than the considered baselines | Markov network structure learning · Distributions from random graphs | Hamming distance | Helped |
| Use the GPM method rather than KCI or GS | Markov network structure learning · Butterfly distributions | Hamming distance | No clear effect |
| Use SCAD sparsity penalty rather than the alternative penalties tested (ablation) | Regularized score matching for GPM estimation · Penalty comparison experiments | structure recovery | Helped |
Closest papers by meaning
- Markov Equivalence and Consistency in Differentiable Structure Learning (NeurIPS 2024 · similarity 0.87)
- Learning Local Neighborhoods of Non-Gaussian Graphical Models (AAAI 2025 · similarity 0.86)
- A Fixed-Parameter Tractable Algorithm for Counting Markov Equivalence Classes with the Same Skeleton (AAAI 2024 · similarity 0.86)
- Distribution Learning Meets Graph Structure Sampling (NeurIPS 2025 · similarity 0.85)
- Graph Neural Networks with a Distribution of Parametrized Graphs (ICML 2024 · similarity 0.85)
- Fast Wasserstein rates for estimating probability distributions of probabilistic graphical models (NeurIPS 2026 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.