Abstract: In this study, physics-informed graph residual learning (PhiGRL) is proposed as an effective and robust deep learning (DL)-based approach for 3-D electromagnetic (EM) modeling. Extended from ...
Abstract: Physics-informed neural networks (PINNs) incorporate physical constraints into their loss functions, allowing them to efficiently solve Partial Differential Equations (PDEs). In this work, ...
A classic math rule now handles infinity. New work strengthens the math behind physics and unbounded systems. % ...
It took 125 years, but in 2025 a team of mathematicians discovered the solution to a long-puzzling problem about the ...
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