SOURCE-LINKED INTELLIGENCE

Recovering Governing Dynamics from Distributed Observations via Exact Spline Merging

arXiv · AI, language, vision and robotics · article · Sep 15, 2026 · UTC

Scientific observations are frequently distributed across locations, time periods, and institutions. Combining such observations into a continuous, differentiable field enables recovering governing physical parameters from its derivatives. This paper makes two contributions in this setting. First, the established additive structure of fixed-basis ridge-regression statistics is applied to tensor-product spline fields: each data holder computes a local Gram matrix and moment vector, and the merged solution is mathematically identical to centralized fitting, with no raw data shared and no iterati

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Evidence & attribution

arXiv · AI, language, vision and robotics · 2026-09-15T03:25:06.000Z

First collected: 2026-09-20T09:01:24.920Z. This is not the publication date.