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Papers/Neurally-plausible radial basis kernels using distributed Fourier embeddings
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Neurally-plausible radial basis kernels using distributed Fourier embeddings

May 8, 2026

arXiv
Abstract

Coherent, continuous spatial representations are critical for synthesizing physical and perceptual phenomena into a single representational space. Radial basis kernels provide a path forward for this type of distributed representation. In this work, we aim to characterize and analyze common radial basis kernels realizable in the neurally-plausible framework of spatial semantic pointers. Further, we analyze previous radial basis kernel work based on grid cell-like representations and demonstrate that such representations are both capable of and optimal for realizing radial basis kernels.

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Authors
Jakeb Chouinard
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arXiv:2605.08458