Article-Journal

RiemannONets: Interpretable neural operators for Riemann problems

Rethinking materials simulations: Blending direct numerical simulations with neural operators

GPT vs Human for Scientific Reviews: A Dual Source Review on Applications of ChatGPT in Science

Deep neural operators can serve as accurate surrogates for shape optimization: a case study for airfoils

Solving inverse heat transfer problems without surrogate models: A fast, data-sparse, physics informed neural network approach

Learning two-phase microstructure evolution using neural operators and autoencoder architectures