Gaussian RBF
PulseAugur coverage of Gaussian RBF — every cluster mentioning Gaussian RBF across labs, papers, and developer communities, ranked by signal.
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ER-KANs: New AI Architecture Boosts Robustness in Data-Scarce Scientific ML
Researchers have introduced ER-KANs, a new type of Kolmogorov-Arnold Network designed for data-scarce scientific machine learning tasks. Unlike existing variants such as ChebyKAN and vanilla KAN, ER-KAN demonstrates sig…
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New method offers total-variation certificates for drifting models
This paper introduces a new method for analyzing drifting models in machine learning, focusing on how to draw conclusions about target and model distributions from noisy, limited data. The proposed approach, Finite-Prob…
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New research clarifies root anti-concentration in online optimization
This paper addresses questions about root anti-concentration in online optimization, specifically for piecewise-Lipschitz functions. The research provides a sharp, dimension-free characterization for homogeneous feature…
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Gaussian RBF RKHS asymptotically approaches Euclidean space, study finds
A new research paper explores the asymptotic behavior of Gaussian RBF reproducing kernel Hilbert spaces (RKHS) and their relationship to Euclidean space. The study demonstrates that in the large bandwidth limit, the Gau…