arXiv Machine Learning
From Numerical Simulators of PDEs to Neural Emulators and Back
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From Numerical Simulators of PDEs to Neural Emulators and Back
Simulation is central to modern engineering and science, but the cost of numerical solvers for partial differential equations (PDEs) remains a bottleneck whenever fast or many-query evaluations are re...
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Are Deep Learning Based Hybrid PDE Solvers Reliable? Why Training Paradigms and Update Strategies Matter
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Operator Boosting Produces Pareto-Efficient PDE Surrogates
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Error-Conditioned Neural Solvers
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Physics-Integrated Operator Learning via Gaussian Splatting Representations
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