Li, Housen

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28.05.2020

NETT: solving inverse problems with deep neuralnetworks

Authors Li H, Schwab J, Antholzer S, Haltmeier M Journal Inverse Problems Citation Inverse Problems 36(2020) 065005 (23pp). Abstract Recovering a function or high-dimensional parameter vector from indirect measurements is a central task in various scientific areas. Several methods for solving such inverse problems are well developed and well understood.
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05.01.2019

Multiscale change-point segmentation: beyond step functions

Authors Li H, Guo Q, Munk A Journal Electronic Journal of Statistics Citation Electron. J. Statist. Volume 13, Number 2 (2019), 3254-3296. Abstract Modern multiscale type segmentation methods are known to detect multiple change-points with high statistical accuracy, while allowing for fast computation. Underpinning (minimax) estimation theory has been developed
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