Call for paper: Machine Learning for Physics: PINNs, CNNs, and Beyond
Lontar Physics Today invites researchers and practitioners to submit original manuscripts for a Special Issue on Machine Learning for Physics: Physics-Informed Neural Networks (PINNs), Convolutional Neural Networks (CNNs), and Beyond. This Special Issue aims to publish rigorous, reproducible work on how neural network–based methods support physics modeling, simulation, inference, and data analysis across theoretical, computational, and experimental contexts.
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