3 papers
cs.LG2026
Real-Time Sensing of Inaccessible Physical Fields via an Edge-Deployable Hardware-Portable Graph Neural Operator
William Howes, Jason Yoo, Kazuma Kobayashi +4
Real-time inference of inaccessible interior physical fields from sparse boundary observations is a fundamental but unresolved problem in scientific machine learning, with direct r…
cs.LG2025
Physics- and geometry-aware spatio-spectral graph neural operator for time-independent and time-dependent PDEs
Subhankar Sarkar, Souvik Chakraborty
Solving partial differential equations (PDEs) efficiently and accurately remains a cornerstone challenge in science and engineering, especially for problems involving complex geome…
cs.LG2024
Spatio-spectral graph neural operator for solving computational mechanics problems on irregular domain and unstructured grid
Subhankar Sarkar, Souvik Chakraborty
Scientific machine learning has seen significant progress with the emergence of operator learning. However, existing methods encounter difficulties when applied to problems on unst…