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A generic explainability architecture for explaining text machine learning models.
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This is a demonstration of peer-to-peer communication structures in multi-agent systems with arguing agents.
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The git repo for Machine-annotated Rationales: Faithfully Explaining Text Classification.
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GUI van de resultaten van een zoekopdracht en GUI van het wijzigen van tags.
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Example plain HTML site using GitLab Pages: https://pages.gitlab.io/plain-html
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Utrecht Engine of Constraint Handling Rules with Priorities
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Prasetya, S.W.B. (Wishnu) / t2
GNU General Public License v3.0 onlyVarious versions of T2, an automated unit testing tool for Java classes. See also T3, the next evolution of T2.
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Alignment of Tip2Tip dataset with the Astra toolbox
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Output data from the experiments performed in the paper "A practical evaluation of Central Trajectories", by Van de Kerkhof, Löffler, and Melssen.
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A program that can be used to create Kakeya sets of dimension two or three. It tries to achieve Kakeya sets which are as small as possible.
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Uncertainty-aware Personal Assistant for Making Personalized Privacy Decisions
A personal privacy assistant (PURE) helps its user make privacy decisions by recommending privacy labels (private or public) for given contents. PURE is unobtrusive, uncertainty-aware, and personalized.
In this repo, you can find how we implement PURE, Standard Neural Networks (SNN), and existing models such as Monte Carlo (MC) dropout and Deep Ensemble.
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This project comprises a template fitting, non-rigid ICP registration framework.
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