HyCOP learns policies over compositions of hybrid modules to produce interpretable programs for parametric PDE solution operators with order-of-magnitude OOD gains over monolithic neural operators.
and Childs, Andrew M
2 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
Adding loop composition to branching quantum walk models produces a variable-time quantum search algorithm whose complexity matches the best known results.
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HyCOP: Hybrid Composition Operators for Interpretable Learning of PDEs
HyCOP learns policies over compositions of hybrid modules to produce interpretable programs for parametric PDE solution operators with order-of-magnitude OOD gains over monolithic neural operators.
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Loop Composition in Quantum Algorithms
Adding loop composition to branching quantum walk models produces a variable-time quantum search algorithm whose complexity matches the best known results.