Hammer Lab for Machine Learning
Machine Learning Group led by Prof. Barbara Hammer at Bielefeld University
Germany
Pinned Repositories
atmn
Automation Toolbox for Machine learning in water Networks
ContrastingExplanationDimRed
"Why Here and Not There?" -- Diverse Contrasting Explanations of Dimensionality Reduction by André Artelt, Alexander Schulz and Barbara Hammer.
efficient_computation_counterfactuals_lvq
Efficient computation of counterfactual explanations of LVQ models by André Artelt and Barbara Hammer
FairnessRobustnessContrastingExplanations
Evaluating Robustness of Counterfactual Explanations by André Artelt, Valerie Vaquet, Riza Velioglu, Fabian Hinder, Johannes Brinkrolf, Malte Schilling and Barbara Hammer
GCNs_for_WDS
Spatial Graph Convolution Neural Networks for Water Distribution Systems
LocalModelAgnosticExamplebasedExplanationsReject
"'I do not Know! But Why?' -- Local Model-Agnostic Example-based Explanations of Reject" by André Artelt, Roel Visser and Barbara Hammer
ModelAgnosticGroupFairnessCounterfactuals
"'Explain it in the Same Way!' -- Model-Agnostic Group Fairness of Counterfactual Explanations" by André Artelt and Barbara Hammer
OnTheComputationOfCounterfactualExplanations
On the computation of counterfactual explanations - A survey by André Artelt and Barbara Hammer
PlausibleAlienZoo
Code, user data, and evaluation scripts for the Plausible Alien Zoo study
UnsupervisedUnlearningConceptDriftAutoencoders
Unsupervised Unlearning of Concept Drift with Autoencoders by André Artelt, Kleanthis Malialis, Christos G. Panayiotou, Marios M. Polycarpou and Barbara Hammer
Hammer Lab for Machine Learning's Repositories
HammerLabML/LocalModelAgnosticExamplebasedExplanationsReject
"'I do not Know! But Why?' -- Local Model-Agnostic Example-based Explanations of Reject" by André Artelt, Roel Visser and Barbara Hammer
HammerLabML/UnsupervisedUnlearningConceptDriftAutoencoders
Unsupervised Unlearning of Concept Drift with Autoencoders by André Artelt, Kleanthis Malialis, Christos G. Panayiotou, Marios M. Polycarpou and Barbara Hammer
HammerLabML/ContrastingExplanationDimRed
"Why Here and Not There?" -- Diverse Contrasting Explanations of Dimensionality Reduction by André Artelt, Alexander Schulz and Barbara Hammer.
HammerLabML/GCNs_for_WDS
Spatial Graph Convolution Neural Networks for Water Distribution Systems
HammerLabML/atmn
Automation Toolbox for Machine learning in water Networks
HammerLabML/ModelAgnosticGroupFairnessCounterfactuals
"'Explain it in the Same Way!' -- Model-Agnostic Group Fairness of Counterfactual Explanations" by André Artelt and Barbara Hammer
HammerLabML/adversarial-edit-attacks
HammerLabML/adversarials_vs_detectors
HammerLabML/ceml
CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
HammerLabML/edist
HammerLabML/java-median-relational-glvq
HammerLabML/java-relational-neural-gas
HammerLabML/linear-transfer-learning
HammerLabML/PLMBiasMeasureBenchmark
HammerLabML/proto-dist-ml
HammerLabML/rmm
HammerLabML/DataPoisoningCounterfactuals
"The Effect of Data Poisoning on Counterfactual Explanations" by André Artelt et al.
HammerLabML/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.
HammerLabML/DRAGON
HammerLabML/EmbeddingBiasScores
Implementations and wrapper of bias scores for text embeddings.
HammerLabML/extending-drift-detection-methods
Extending Drift Detection Methods to Identify When Exactly the Change Happened
HammerLabML/FairnessInWDNs
Fairness-enhancing machine learning methods in the domain of water distribution networks.
HammerLabML/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.
HammerLabML/IntroAlienZoo
Introducing the Alien Zoo approach: An experimental framework for evaluating counterfactual explanations for ML
HammerLabML/iXAI
Fast and incremental explanations for online machine learning models. Works best with the river framework.
HammerLabML/MeasuringFairnessWithBiasedData
HammerLabML/physics_informed_gnns_for_wds
Official code for the paper: Physics-Informed Graph Neural Networks for Water Distribution Systems
HammerLabML/SAM-MLKR
Code for the paper 'Interpretable SAM-kNN Regressor for Incremental Learning on High-Dimensional Data Streams'
HammerLabML/shapiq
HammerLabML/TwoStageMultiinstCFs
"A Two-Stage Algorithm for Cost-Efficient Multi-instance Counterfactual Explanations" by Artelt et al.