Decomposition for Bayesian Networks: Local and Parallel Inference

arXiv:2607.04650 · stat.ML, cs.LG · Submitted 2026-07-06 · Read on arXiv

Pei Heng, Xinyi Hu, Yi Sun

stat.ML, cs.LG

Submitted: 2026-07-06

Comments: 13 pages, 5 figures,Code available at https://github.com/Balance-H/Decomposition-for-BNs

Journal ref: IEEE Transactions on Pattern Analysis and Machine Intelligence, 2026

DOI: 10.1109/TPAMI.2026.3704481

Code: https://github.com/Balance-H/Decomposition-for-BNs

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

Terminology

• Pruning — 10× in this paper · explained in 4 episodes
• Accuracy — 8× in this paper · explained in 1 episode
• Computational Efficiency — 3× in this paper · explained in 2 episodes
• Dimensionality Reduction — 3× in this paper · explained in 2 episodes
• Benchmark — 2× in this paper · explained in 2 episodes
• Conditional Independence — 2× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Kullback–Leibler Divergence — 2× in this paper · explained in 2 episodes
• Causal Inference — 1× in this paper · explained in 5 episodes
• Computational overhead — 1× in this paper · explained in 2 episodes
• Directed Acyclic Graph (DAG) — 1× in this paper · explained in 2 episodes
• EMMA — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 5 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Structural Dimension Reduction in Bayesian Networks

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