Author

Letian Chen

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Preprint Aug 2026

Continual-Learning Physics-Informed Neural Networks for Parameterized Partial Differential Equations

A continual-learning physics-informed neural network (CL-PINN), which combines Bayesian-optimization-based active parameter selection, task-wise dynamic loss weighting, sparse physics-constrained replay, and an optional parameter subnetwork to improve task allocation and knowledge retention under bounded active-task capacity.

Xujia Chen, Xinyu Hu, Letian Chen et al. · 0 citations