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@@ -48,190 +48,11 @@ Inversion algorithms:
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*[InverseAlgos.jl](https://github.com/GinvLab/InverseAlgos.jl)[[docs](https://ginvlab.github.io/InverseAlgos.jl)] Inversion algorithm subdivided in three sub-modules/categories:
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-**Hamiltonian Monte Carlo** and "classic" **Metropolis-Hastings** samplers. Includes the "plain" HMC, the NUTS algorithms et al..
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-**Optimization**. Currently only the L-BFGS algorithm (with optional box constraints) is implemented.
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-**Optimization**. Currently the L-BFGS and Gauss-Newton algorithms (with optional box constraints) are implemented.
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-**Linear inverse problems under Gaussian uncertainties**. Kronecker product-based inversion (`KronLinInv`) and classic least squares.
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Examples/tutorials:
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*[GinvLab-examples](https://github.com/GinvLab/GinvLab-examples.jl)[[docs](https://ginvlab.github.io/GinvLab-examples.jl)] A set of scripts and Jupyter notebooks illustrating some simple example problems solved using the packages part of G⁻¹Lab.
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<!-- * \biblabel{bezanson17}{Bezanson et al. (2017)} **Bezanson**, **Edelman**, **Karpinski** and **Shah**, [Julia: a fresh approach to numerical computing](https://julialang.org/research/julia-fresh-approach-BEKS.pdf), SIAM review 2017. -->
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