Across 12 fixed-hyperparameter tabular benchmarks, KANs beat MLPs on 9/12 datasets in accuracy and 10/12 in F1, yet cost ~16x parameters; the paper's significance tests are internally inconsistent.
In: International Conference on Artificial Neural Networks
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Is the Statistical Advantage Worth the Cost? An Empirical Comparison of KANs and MLPs for Structured Data Classification
Across 12 fixed-hyperparameter tabular benchmarks, KANs beat MLPs on 9/12 datasets in accuracy and 10/12 in F1, yet cost ~16x parameters; the paper's significance tests are internally inconsistent.