arXiv (All)
open access
Mesh-Free Numerical Approximation of the Biharmonic Equation via Optimized Kolmogorov--Arnold Neural Networks
A mesh-free numerical framework based on \textit{Kolmogorov--Arnold Physics-Informed Neural Networks} (KAN-PINNs) is developed for the approximation of fourth-order elliptic boundary value problems, with specific application to the biharmonic equation governing thin plate deflection. Unlike conventi
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- An arbitrary-order BGG-based discrete scheme for the Reissner--Mindlin plate problem on polygonal meshes#1123512
- Nonconforming virtual element method for the Monge-Ampère equation#985060
- Analytical properties of polygonal Stokes and BGG Hessian complexes with application to Kirchhoff--Love plates#997061
- Non-linear elastic micro-dilatation theory: Matrix exponential function paradigm#676982
- Eulerian triangulations: two-point function and hull perimeter statistics#997868
Record · ID 1144436
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive