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 😃
Hammer Lab for Machine Learning
Machine Learning Group led by Prof. Barbara Hammer at Bielefeld University
Popular repositories
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UnsupervisedUnlearningConceptDriftAutoencoders
UnsupervisedUnlearningConceptDriftAutoencoders PublicUnsupervised Unlearning of Concept Drift with Autoencoders by André Artelt, Kleanthis Malialis, Christos G. Panayiotou, Marios M. Polycarpou and Barbara Hammer
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LocalModelAgnosticExamplebasedExplanationsReject
LocalModelAgnosticExamplebasedExplanationsReject Public"'I do not Know! But Why?' -- Local Model-Agnostic Example-based Explanations of Reject" by André Artelt, Roel Visser and Barbara Hammer
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OnTheComputationOfCounterfactualExplanations
OnTheComputationOfCounterfactualExplanations PublicOn the computation of counterfactual explanations - A survey by André Artelt and Barbara Hammer
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FairnessRobustnessContrastingExplanations
FairnessRobustnessContrastingExplanations PublicEvaluating Robustness of Counterfactual Explanations by André Artelt, Valerie Vaquet, Riza Velioglu, Fabian Hinder, Johannes Brinkrolf, Malte Schilling and Barbara Hammer
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ContrastingExplanationDimRed
ContrastingExplanationDimRed Public"Why Here and Not There?" -- Diverse Contrasting Explanations of Dimensionality Reduction by André Artelt, Alexander Schulz and Barbara Hammer.
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efficient_computation_counterfactuals_lvq
efficient_computation_counterfactuals_lvq PublicEfficient computation of counterfactual explanations of LVQ models by André Artelt and Barbara Hammer
Repositories
Showing 10 of 45 repositories
- DataPoisoningCounterfactuals Public Forked from andreArtelt/DataPoisoningCounterfactuals
"The Effect of Data Poisoning on Counterfactual Explanations" by André Artelt et al.
- TwoStageMultiinstCFs Public Forked from andreArtelt/TwoStageMultiinstCFs
"A Two-Stage Algorithm for Cost-Efficient Multi-instance Counterfactual Explanations" by Artelt et al.
- PLMBiasMeasureBenchmark Public
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- DeepView Public Forked from LucaHermes/DeepView
This is an implementation of the DeepView framework that was presented in the paper Schulz, A., Hinder, F., & Hammer, B. (2020): https://www.ijcai.org/Proceedings/2020/319. Also available on Arxiv (2019 version): https://arxiv.org/abs/1909.09154.
- geoconv Public Forked from andreasMazur/geoconv
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.
- ceml Public Forked from andreArtelt/ceml
CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
- physics_informed_gnns_for_wds Public Forked from inaamashraf/physics_informed_gnns_for_wds
Official code for the paper: Physics-Informed Graph Neural Networks for Water Distribution Systems
- IntroAlienZoo Public Forked from ukuhl/IntroAlienZoo
Introducing the Alien Zoo approach: An experimental framework for evaluating counterfactual explanations for ML
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