DeSyR: A Decoupled Symbolic Recovery Framework with PINN-Guided Structure Search and Physics-Informed Coefficient Refinement

arXiv:2609.00530 · cs.LG · Submitted 2026-09-01 · Read on arXiv

cs.LG

Submitted: 2026-09-01

Updated: 2026-09-01

Terminology

• Verification — 38× in this paper · explained in 2 episodes
• Benchmark — 23× in this paper · explained in 2 episodes
• Symbolic Regression — 16× in this paper · explained in 5 episodes
• Accuracy — 14× in this paper · explained in 1 episode
• Consistency — 12× in this paper · explained in 3 episodes
• Ablation — 11× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Convergence Guarantees — 3× in this paper · explained in 3 episodes
• Decoupling — 3× in this paper · explained in 2 episodes
• Pruning — 3× in this paper · explained in 4 episodes
• Adam — 2× in this paper · explained in 2 episodes
• DeepONet — 2× in this paper · explained in 2 episodes
• Distillation — 2× in this paper · explained in 2 episodes
• Initial Data — 2× in this paper · explained in 2 episodes
• Physical Constraints — 2× in this paper · explained in 7 episodes
• Trace — 2× in this paper · explained in 2 episodes
• Adaptive Reweighting — 1× in this paper · explained in 1 episode
• Adaptive Sampling — 1× in this paper · explained in 1 episode
• Error Decomposition — 1× in this paper · explained in 3 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Interpretability — 1× in this paper · explained in 15 episodes
• Physics-Informed Neural Network (PINN) — 1× in this paper · explained in 3 episodes
• Physics-Informed Neural Networks (PINNs) — 1× in this paper · explained in 6 episodes
• Verifiability — 1× in this paper · explained in 2 episodes

Sources

• Fourier Neural Operator for Parametric Partial Differential Equations
• Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl
• Deep symbolic regression: Recovering mathematical expressions from data via risk-seeking policy gradients
• Symbolic Regression for PDEs using Pruned Differentiable Programs
• SymTorch: Symbolic Distillation of Neural Networks
• Physics Informed Symbolic Networks
• StruSR: Structure-Aware Symbolic Regression with Physics-Informed Taylor Guidance
• A Data-Free Symbolic Regression Approach for Solving Equations
• Genetic Programming Based Symbolic Regression for Analytical Solutions to Differential Equations

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