AI RESEARCH
Physics-Informed Deep B-Spline Networks
arXiv CS.LG
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ArXi:2503.16777v3 Announce Type: replace Physics-informed machine learning offers a promising framework for solving complex partial differential equations (PDEs) by integrating observational data with governing physical laws. However, learning PDEs with varying parameters and changing initial conditions and boundary conditions (ICBCs) with theoretical guarantees remains an open challenge.