Spatio-spectral graph neural operator for solving computational mechanics problems on irregular domain and unstructured grid
S Sarkar, S Chakraborty - Computer Methods in Applied Mechanics and …, 2025 - Elsevier
Scientific machine learning has seen significant progress with the emergence of operator
learning. However, existing methods encounter difficulties when applied to problems on …
learning. However, existing methods encounter difficulties when applied to problems on …
A general reduced-order neural operator for spatio-temporal predictive learning on complex spatial domains
Predictive learning for spatio-temporal processes (PL-STP) on complex spatial domains
plays a critical role in various scientific and engineering fields, with its essence being the …
plays a critical role in various scientific and engineering fields, with its essence being the …
Enhancing multiscale simulations with constitutive relations‐aware deep operator networks
Multiscale problems are widely observed across diverse domains in physics and
engineering. Translating these problems into numerical simulations and solving them using …
engineering. Translating these problems into numerical simulations and solving them using …