Multi-output Gaussian process prediction of physical fields under linear equality constraints

arXiv:2608.25709 · stat.ML, cs.LG · Submitted 2026-08-26 · Read on arXiv

stat.ML, cs.LG

Submitted: 2026-08-26

Updated: 2026-08-26

Code: https://github.com/nasrmht/paper_benchmark_repo

Terminology

• Latent Space — 14× in this paper · explained in 7 episodes
• Reconstruction Error — 11× in this paper · explained in 2 episodes
• Benchmark — 10× in this paper · explained in 2 episodes
• Accuracy — 9× in this paper · explained in 1 episode
• Generalization — 8× in this paper · explained in 13 episodes
• Uncertainty Quantification — 7× in this paper · explained in 8 episodes
• Calibration — 5× in this paper · explained in 7 episodes
• Principal Component Analysis — 5× in this paper
• Computational Fluid Dynamics — 4× in this paper
• Alignment — 3× in this paper · explained in 1 episode
• Spectral Gap — 3× in this paper · explained in 5 episodes
• Core — 2× in this paper · explained in 2 episodes
• Empirical Coverage — 2× in this paper · explained in 2 episodes
• Latent Representation — 2× in this paper · explained in 2 episodes
• Latent Representations — 2× in this paper · explained in 3 episodes
• Root Mean Square Error — 2× in this paper
• Trace — 2× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 4 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Fidelity — 1× in this paper · explained in 2 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Kernel Density Estimation — 1× in this paper
• Multi-Output Gaussian Processes — 1× in this paper
• Relative Root Mean Square Error — 1× in this paper
• Singular Value Decomposition (SVD) — 1× in this paper · explained in 2 episodes
• Spatial Relative Squared Error — 1× in this paper
• Unified Framework — 1× in this paper · explained in 5 episodes

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