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  "Title": "Linear p-Wasserstein Projections",
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  "Description": "Performs Wasserstein projections from the predictive\ndistributions of any model into the space of predictive\ndistributions of linear models. We utilize L1 penalties to also\nreduce the complexity of the model space. This package employs\nthe methods as described in Dunipace, Eric and Lorenzo Trippa\n(2020) <doi:10.48550/arXiv.2012.09999>.",
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  "Date/Publication": "2025-06-10 04:36:15 UTC",
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  "Author": "Eric Dunipace [aut, cre] (ORCID:\n<https://orcid.org/0000-0001-8909-213X>),\nClemens Schmid [ctb] (ORCID: <https://orcid.org/0000-0003-3448-5715>,\nETA progres bar is adapted from their code),\nEspen Bernton [ctb] ('Hilbert Sort' adapted from their code),\nMathieu Gerber [ctb] ('Hilbert Sort' adapted from their code),\nPierre Jacob [ctb] ('Hilbert Sort' adapted from their code),\nBin Dai [ctb] (W2 projections adapted from their 'OEM' code),\nJared Huling [ctb] (ORCID: <https://orcid.org/0000-0003-0670-4845>, W2\nprojections adapted from their 'OEM' code),\nYixuan Qiu [ctb] (W2 projections adapted from their 'OEM' code),\nDominic Schuhmacher [ctb] ('Shortsimplex 'optimal transport method\nadapted from their code),\nNicolas Bonneel [ctb] ('Network Simplex' algorithm adapted from their\ncode)",
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