Hammer Lab for Machine Learning
Machine Learning Group led by Prof. Barbara Hammer at Bielefeld University
Germany
Pinned Repositories
ceml
CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
EPyT-Flow
A high-level interface designed for the easy generation of hydraulic and water quality scenario data.
GCNs_for_WDS
Spatial Graph Convolution Neural Networks for Water Distribution Systems
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.
iXAI
Fast and incremental explanations for online machine learning models. Works best with the river framework.
LocalModelAgnosticExamplebasedExplanationsReject
"'I do not Know! But Why?' -- Local Model-Agnostic Example-based Explanations of Reject" by André Artelt, Roel Visser and Barbara Hammer
OnTheComputationOfCounterfactualExplanations
On the computation of counterfactual explanations - A survey by André Artelt and Barbara Hammer
shapiq-package
Shapley Interactions for Machine Learning
UnsupervisedUnlearningConceptDriftAutoencoders
Unsupervised Unlearning of Concept Drift with Autoencoders by André Artelt, Kleanthis Malialis, Christos G. Panayiotou, Marios M. Polycarpou and Barbara Hammer
WaterBenchmarkHub
A collection of benchmark resources regarding Water Distribution Networks
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/WaterBenchmarkHub
A collection of benchmark resources regarding Water Distribution Networks
HammerLabML/adversarials_vs_detectors
HammerLabML/ceml
CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox
HammerLabML/EPyT-Flow
A high-level interface designed for the easy generation of hydraulic and water quality scenario data.
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/iXAI
Fast and incremental explanations for online machine learning models. Works best with the river framework.
HammerLabML/java-median-relational-glvq
HammerLabML/PLMBiasMeasureBenchmark
HammerLabML/shapiq-package
Shapley Interactions for Machine Learning
HammerLabML/AnalyzingInfluenceTrainingSamplesExplanations
"Analyzing the Influence of Training Samples on Explanations" by André Artelt et al.
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/FairnessInWDSs_extended
Fairness-enhancing machine learning methods in the domain of water distribution networks (extended version).
HammerLabML/fashionfail
Official repository of "FashionFail: Addressing Failure Cases in Fashion Object Detection and Segmentation".
HammerLabML/IntroAlienZoo
Introducing the Alien Zoo approach: An experimental framework for evaluating counterfactual explanations for ML
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.