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cs.LG2025
A Surrogate model for High Temperature Superconducting Magnets to Predict Current Distribution with Neural Network
Mianjun Xiao, Peng Song, Yulong Liu +7
Finite element methods (FEM) for high-temperature superconducting (HTS) magnets become time-consuming at larger scales, restricting the rapid optimization of meter-scale REBCO sole…
cs.LG2023
GBM-based Bregman Proximal Algorithms for Constrained Learning
Zhenwei Lin, Qi Deng
As the complexity of learning tasks surges, modern machine learning encounters a new constrained learning paradigm characterized by more intricate and data-driven function constrai…