A stochastic gradient descent approach with partitioned-truncated singular value decomposition for large-scale inverse problems of magnetic modulus data

DOI10.1088/1361-6420/ac6a03zbMath1489.86013arXiv2201.03964OpenAlexW4221141363MaRDI QIDQ5081796

Kangzhi Wang, Ting-Ting Fan, Wenbin Li

Publication date: 17 June 2022

Published in: Inverse Problems (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2201.03964

zbMATH Keywords

stochastic gradient descentlarge-scale inverse problemmagnetic modulus datapartitioned-truncated SVD

Mathematics Subject Classification ID

Inverse problems in geophysics (86A22) Geo-electricity and geomagnetism (86A25)

Related Items (1)

Uniformly convex neural networks and non-stationary iterated network Tikhonov (iNETT) method

Cites Work

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