Accelerating Eigenvalue Dataset Generation via Chebyshev Subspace Filter

ArXi:2510.23215v2 Announce Type: replace Eigenvalue problems are among the most important topics in many scientific disciplines. With the recent surge and development of machine learning, neural eigenvalue methods have attracted significant attention as a forward pass of inference requires only a tiny fraction of the computation time compared to traditional solvers. However, a key limitation is the requirement for large amounts of labeled data in