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actionablecounterfactualsconvexprogramming

Convex optimization for actionable & plausible counterfactual explanations by André Artelt and Barbara Hammer

adversarial-edit-attacks

adversarials_vs_detectors

atmn

Automation Toolbox for Machine learning in water Networks

ceml

CEML - Counterfactuals for Explaining Machine Learning models - A Python toolbox

contrastingexplanationdimred

"Why Here and Not There?" -- Diverse Contrasting Explanations of Dimensionality Reduction by André Artelt, Alexander Schulz and Barbara Hammer.

contrastive_explanations

Efficient computation of contrastive explanations by André Artelt and Barbara Hammer

contrastiveexplanationsformodeladaptations

Contrastive Explanations for Explaining Model Adaptations by André Artelt, Fabian Hinder, Valerie Vaquet, Robert Feldhans and Barbara Hammer

convexdensityconstraintsforplausiblecounterfactuals

Convex Density Constraints for Computing Plausible Counterfactual Explanations by André Artelt and Barbara Hammer

datapoisoningcounterfactuals

"The Effect of Data Poisoning on Counterfactual Explanations" by André Artelt et al.

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.

diversesemifactualsreject

"Even if ..." -- Diverse Semifactual Explanations of Reject by André Artelt and Barbara Hammer.

dragon

edist

efficient_computation_counterfactuals_lvq

Efficient computation of counterfactual explanations of LVQ models by André Artelt and Barbara Hammer

embeddingbiasscores

Implementations and wrapper of bias scores for text embeddings.

ensembleconsistentexplanations

One Explanation to Rule them All -- Ensemble Consistent Explanations by André Artelt, Stelios Vrachimis, Demetrios Eliades, Marios Polycarpou and Barbara Hammer

explaining_lvq_reject

Explaining Reject Options of Learning Vector Quantization Classifiers by André Artelt, Johannes Brinkrolf, Roel Visser and Barbara Hammer

extending-drift-detection-methods

Extending Drift Detection Methods to Identify When Exactly the Change Happened

fairnessinwdns

Fairness-enhancing machine learning methods in the domain of water distribution networks.

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

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.

graph-edit-networks

introalienzoo

Introducing the Alien Zoo approach: An experimental framework for evaluating counterfactual explanations for ML

ixai

Fast and incremental explanations for online machine learning models. Works best with the river framework.

java-median-relational-glvq

java-relational-neural-gas

linear-transfer-learning