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Transfer learning for improved generalizability in causal physics-informed neural networks for beam simulations
Neural Oscillators for Generalization of Physics-Informed Machine Learning
Physics-Informed Neural Networks for Solving Forward and Inverse Problems in Complex Beam Systems
Predicting traction return current in electric railway systems through physics-informed neural networks
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