16 citations · 16 across the 4 of their papers we have counts for
4 papers
Adaptive RBF-KAN: A Comparative Evaluation of Dynamic Shape Parameters in Kolmogorov-Arnold Networks
Roberto Cavoretto, Alessandra De Rossi, Adeeba Haider +1
Kolmogorov-Arnold Networks (KANs) approximate multivariate functions using learnable univariate edge functions, typically parameterized by B-spline bases. Although effective, splin…
Making Gaussian Kolmogorov-Arnold Networks Reliable and Accurate
Amir Noorizadegan, Sifan Wang, Leevan Ling
Kolmogorov-Arnold Networks (KANs) replace fixed activations with learnable univariate edge functions whose behavior depends strongly on the chosen basis. Gaussian radial basis func…
Highway Networks for Improved Surface Reconstruction: The Role of Residuals and Weight Updates
A. Noorizadegan, Y. C. Hon, D. L. Young +1
Surface reconstruction from point clouds is a fundamental challenge in computer graphics and medical imaging. In this paper, we explore the application of advanced neural network a…
Power-Enhanced Residual Network for Function Approximation and Physics-Informed Inverse Problems
Amir Noorizadegan, D. L. Young, Y. C. Hon +1
In this study, we investigate how the updating of weights during forward operation and the computation of gradients during backpropagation impact the optimization process, training…