INRs parameterize signals as neural networks to enable continuous representations, analytical differentiation, and adaptive approximation spaces that address spectral bias through specialized activations and structured encodings.
Implicit neural representation as vectorizer for classification task applied to diverse data structures,
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Implicit Neural Representations: A Signal Processing Perspective
INRs parameterize signals as neural networks to enable continuous representations, analytical differentiation, and adaptive approximation spaces that address spectral bias through specialized activations and structured encodings.