5 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 4 cited
Attention-enhanced neural differential equations for physics-informed deep learning of ion transport
Danyal Rehman, John H. Lienhard
Species transport models typically combine partial differential equations (PDEs) with relations from hindered transport theory to quantify electromigrative, convective, and diffusi…
cs.LG2023★ 5 cited
Physics-constrained neural differential equations for learning multi-ionic transport
Danyal Rehman, John H. Lienhard
Continuum models for ion transport through polyamide nanopores require solving partial differential equations (PDEs) through complex pore geometries. Resolving spatiotemporal featu…