S-NOT, a GRU-transformer hybrid, predicts full-field solutions of time-dependent nonlinear PDEs with lower error than Sequential DeepONet on steel solidification, 3D lug, and dogbone benchmarks.
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Sequential Neural Operator Transformer for High-Fidelity Surrogates of Time-Dependent Non-linear Partial Differential Equations
S-NOT, a GRU-transformer hybrid, predicts full-field solutions of time-dependent nonlinear PDEs with lower error than Sequential DeepONet on steel solidification, 3D lug, and dogbone benchmarks.