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Curvature-Aware Training for Coordinate Networks
Coordinate networks are widely used in computer vision due to their ability to represent signals as compressed, continuous entities.
On Quantizing Implicit Neural Representations
The role of quantization within implicit/coordinate neural networks is still not fully understood.
How You Start Matters for Generalization
Characterizing the remarkable generalization properties of over-parameterized neural networks remains an open problem.
On Regularizing Coordinate-MLPs
We show that typical implicit regularization assumptions for deep neural networks (for regression) do not hold for coordinate-MLPs, a family of MLPs that are now ubiquitous in computer vision for representing high-frequency signals.
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