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Warning
Work in progress!
Probabilistic and deterministic inverse algorithms for geophysical problems and beyond. This package can be used in combination with the other packages addressing geophysical problems as part of G⁻¹Lab.
InverseAlgos is an unbrella package currently including three sub-modules:
Samplers: (Hamiltonian) Monte Carlo sampling algorithms (formerly part of HMCLab)Optimizers: deterministic gradient-based algorithms, currently including l-BFGS and Gauss-Newton algosKronLinInv: Kronecker-product-based least squares inversion under Gaussian and separability assumptions
See the following publications:
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Andrea Zunino, Lars Gebraad, Alessandro Ghirotto, Andreas Fichtner (2023), HMCLab: a framework for solving diverse geophysical inverse problems using the Hamiltonian Monte Carlo method, Geophysical Journal International, Volume 235, Issue 3, Pages 2979–2991, https://doi.org/10.1093/gji/ggad403
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Andrea Zunino, Klaus Mosegaard (2019), An efficient method to solve large linearizable inverse problems under Gaussian and separability assumptions, Computers & Geosciences. ISSN 0098-3004, https://doi.org/10.1016/j.cageo.2018.09.005.