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Models that solve differential equations often use neural networks, but this work uses trainable spline representations instead. This approach directly parametrizes the solution, which could be more efficient. The real test is whether it holds up outside the lab.
“arXiv:2607.15751v1 Announce Type: new Abstract: This work introduces Physics-Informed Splines (PI-Splines), a structured spline-based architecture for physics-informed learning. Instead of representing the solution of a differential equatio…”
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Physics-Informed Splines, arXiv
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Aug 5, 2026