We are the Machine Learning Group led by Prof. Barbara Hammer at Bielefeld University.
On this page you can find the accompanying source code of our publications 😃
We are the Machine Learning Group led by Prof. Barbara Hammer at Bielefeld University.
On this page you can find the accompanying source code of our publications 😃
A high-level interface designed for the easy generation of hydraulic and water quality scenario data.
A collection of benchmark resources regarding Water Distribution Networks
Fairness-enhancing machine learning methods in the domain of water distribution networks (extended version).
"Analyzing the Influence of Training Samples on Explanations" by André Artelt et al.
CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
Official repository of "FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation".
A Python library for end-to-end learning on surfaces. It implements pre-processing functions that include geodesic algorithms, neural network layers that operate on surfaces, visualization tools and benchmarking functionalities.
"The Effect of Data Poisoning on Counterfactual Explanations" by André Artelt et al.