Efficient Message Passing for Partial Differential Equation Priors

arXiv:2609.32956 · cs.LG, cs.AI, stat.ML · Submitted 2026-09-26 · Read on arXiv

cs.LG, cs.AI, stat.ML

Submitted: 2026-09-26

Updated: 2026-09-26

Terminology

• PDE residual — 17× in this paper · explained in 2 episodes
• Activation Function — 12× in this paper · explained in 1 episode
• Ablation — 7× in this paper · explained in 1 episode
• Accuracy — 5× in this paper · explained in 1 episode
• Calibration — 5× in this paper · explained in 7 episodes
• Ablation study — 4× in this paper · explained in 1 episode
• Empirical Coverage — 4× in this paper · explained in 2 episodes
• Adam — 3× in this paper · explained in 2 episodes
• Bayesian Inference — 3× in this paper · explained in 5 episodes
• Generative AI — 3× in this paper · explained in 2 episodes
• Hamiltonian Monte Carlo — 3× in this paper
• Failure Modes — 2× in this paper · explained in 3 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Inverse Problem — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Principal Component Analysis (PCA) — 1× in this paper · explained in 4 episodes
• Stochastic Gradient Descent (SGD) — 1× in this paper · explained in 5 episodes
• Uncertainty Quantification — 1× in this paper · explained in 8 episodes

Sources

• Direct Message Approximation (DMA): A Consistency-Based Framework for Tractable Approximate Inference on Factor Graphs

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