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cs.LG2026
ArGEnT: Arbitrary Geometry-encoded Transformer for Operator Learning
Wenqian Chen, Yucheng Fu, Zhi-Feng Wei +3
Learning solution operators on arbitrary geometries remains a central challenge in scientific machine learning, especially for many-query simulation, physics-informed learning, and…
cs.LG2024
Adaptive Interface-PINNs (AdaI-PINNs): An Efficient Physics-informed Neural Networks Framework for Interface Problems
Sumanta Roy, Chandrasekhar Annavarapu, Pratanu Roy +1
We present an efficient physics-informed neural networks (PINNs) framework, termed Adaptive Interface-PINNs (AdaI-PINNs), to improve the modeling of interface problems with discont…