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math.NA2026
Dimension-independent eigenvalue approximation for sparse matrices
Natalia Hajlasz, Christopher Musco, Jonathan Weare +1
Many applications in science and engineering require solving sparse Hermitian eigenvalue problems that are so large that even algorithms whose runtime scales linearly with the matr…
physics.ao-ph2026
Explaining El Niño Forecasts with the Average Gradient Outer Product
Yuan Hui, Dorian S. Abbot, Robert J. Webber
An important and unresolved problem in the physical sciences is explaining the predictions made by neural networks. Several explainable artificial intelligence (XAI) methods have b…