SincKANs integrate Sinc interpolation into KAN activations and report better empirical results than alternatives on function approximation and PINN tasks.
Adaptive training of grid-dependent physics-informed kolmogorov-arnold networks, 2024
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ActNet is a new KST-based neural network that outperforms KANs and competes with MLPs in PINN benchmarks for PDE simulation tasks.
A systematic review of Kolmogorov-Arnold Networks that maps their relation to Kolmogorov superposition theory, MLPs, and kernels, examines basis-function design choices, summarizes performance advances, and supplies a practitioner's selection guide plus open challenges.
citing papers explorer
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Sinc Kolmogorov-Arnold Network and Its Applications on Physics-informed Neural Networks
SincKANs integrate Sinc interpolation into KAN activations and report better empirical results than alternatives on function approximation and PINN tasks.
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Deep Learning Alternatives of the Kolmogorov Superposition Theorem
ActNet is a new KST-based neural network that outperforms KANs and competes with MLPs in PINN benchmarks for PDE simulation tasks.
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A Practitioner's Guide to Kolmogorov-Arnold Networks
A systematic review of Kolmogorov-Arnold Networks that maps their relation to Kolmogorov superposition theory, MLPs, and kernels, examines basis-function design choices, summarizes performance advances, and supplies a practitioner's selection guide plus open challenges.