Learning rocking dynamics from sparse shake‐table data with interpretable physics‐Informed neural networks

We present a hybrid interpretable Physics-Informed Neural Network Long-Short Term Memory (Hybrid PINN LSTM) framework for predicting the seismic response of rocking blocks. Existing analytical models rely on uncertain idealizations, while purely data-driven and machine-learning approaches lack physi