Explore projects
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Extension of text_explainability for sensitivity testing (robustness & fairness).
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BSC project done by Joep Robben on "Deep learning steerable projections using a supervised modular neural network", Supervised by Michael Behrisch
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A generic explainability architecture for explaining text machine learning models.
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2023-01 Project by Oscar Fickel and supervised by Peter Vangorp
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A tool used to interact and understand dimensionality reduced data. It can be used to generate, view and explain point clouds!
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Containerized LOLA image for analyzing Petri nets via endpoint.
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Use any lat-lon mapped data to create a dodecahedron globe
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This is a project to write an all python seismic tomography toolbox as a teaching tool. This project will provide the codes and file architecture to use an integration over the path methodology with Voronoi cells.
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This project is maintained by Dylan Kruyff, Yuncong Yu and Michael Behrisch,
Fast local pattern search in multivariate time series with query-aware locality-sensitive hashing and relevance feedback.
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