The Mechanics of Delta Learning: Target Design for Generalizable Scientific Machine Learning

arXiv:2609.28782 · cs.LG, physics.chem-ph, physics.comp-ph · Submitted 2026-09-23 · Read on arXiv

cs.LG, physics.chem-ph, physics.comp-ph

Submitted: 2026-09-23

Updated: 2026-09-23

Code: https://github.com/kareem-gameel/delta-learning-target-design

Terminology

• Accuracy — 19× in this paper · explained in 1 episode
• Alignment — 11× in this paper · explained in 1 episode
• GNNs — 6× in this paper · explained in 2 episodes
• Fidelity — 5× in this paper · explained in 2 episodes
• Generalization — 5× in this paper · explained in 13 episodes
• Calibration — 3× in this paper · explained in 7 episodes
• Regularization — 3× in this paper · explained in 3 episodes
• Transferability — 3× in this paper · explained in 4 episodes
• Domain Shift — 2× in this paper · explained in 4 episodes
• Generalizability — 2× in this paper · explained in 6 episodes
• Pair-Radial Expansion — 2× in this paper
• Reconstruction Error — 2× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Core — 1× in this paper · explained in 2 episodes
• Frozen model — 1× in this paper · explained in 3 episodes
• Graph Neural Network (GNN) — 1× in this paper · explained in 3 episodes
• Provenance — 1× in this paper · explained in 4 episodes
• Robustness — 1× in this paper · explained in 5 episodes

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