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Unifying-machine-learning-and-interpolation-theory-via-interpolating-neural-networks

Unifying machine learning and interpolation theory via interpolating neural networks

Introduction Emerging scientific computational methods are moving from relying on explicitly defined and modular programming to the adoption of neural network-based self-corrective algorithms. In computer science, this transition is coined as “from Software 1.0 to Software 2.0”1. The shift towards software 2.0 partially resolves the issue of labor-intensive programming in Software 1.0 and has significantly
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