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This code is unmaintained and relates to v0.x of GraphPolaris. Use frontent_v2 instead

Project by Oscar Alexander Kirschstein Schäfer

Project start: 12/2022 Supervised by Michael Behrisch and Yuncong Yu

Containerized LOLA image for analyzing Petri nets via endpoint.

Here are the code and data files placed which I used for the publication in JGR:oceans about the effect of freshwater pulses on estuarine salinity.

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.

This is a demo repository!