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News/From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data
arxiv
PublishedJuly 24, 2026 at 4:00 AM

From Scalars to Time Series: Rethinking Implicit Neural Representations for Time-Varying Volumetric Data

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arXiv:2607.20970v1 Announce Type: new Abstract: Implicit neural representations (INRs) for time-varying volumetric data are typically trained using dense sampling over spatiotemporal coordinates, where each observation corresponds to a single point in space and time. This coordinate-wise formulation

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