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ADAPT : Awesome Domain Adaptation Python Toolbox

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arxiv 2107.03049 v2 pith:HFENZ4S6 submitted 2021-07-07 cs.LG

Antoine de Mathelin , Mounir Atiq , Guillaume Richard , Alejandro de la Concha , Mouad Yachouti , François Deheeger , Mathilde Mougeot , Nicolas Vayatis This is my paper · ORCID
classification cs.LG
keywords adaptadaptationdomainlibrarypythonaccessadapt-pythonapproach
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In this paper, we introduce the ADAPT library, an open source Python API providing the implementation of the main transfer learning and domain adaptation methods. The library is designed with a user friendly approach to facilitate the access to domain adaptation for a wide public. ADAPT is compatible with scikit-learn and TensorFlow and a full documentation is proposed online https://adapt-python.github.io/adapt/ with a substantial gallery of examples.

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  1. Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions

    cs.LG 2024-11 conditional novelty 6.0 of 10

    A biased-splitting plus reweighting evaluation method, Vertical Validation, tests whether implicit graph generators can match held-out data in thinly supported regions and selects models that generalize there.

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