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Private Dynamical Linear Upper Confidence Bound (DynLin-UCB)
The repository contains the code to run DynLin-UCB (Dynamical Linear Upper Confidence Bound). DynLin-UCB is an optimistic regret-minimization algorithm that can be used to... -
Debiaser for Multiple Variables (DEMV)
DEMV is a Debiaser for Multiple Variables that aims to increase Fairness in any given dataset, both binary and categorical, with one or more sensitive variables, while keeping...-
ipynb
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ipynb
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TriplEx - Explaining with Triples
TRIPLEX is an explainability package for Transformer-based models fine-tuned on Natural Language Inference, Semantic Text Similarity, or Text Classification tasks. TRIPLEX... -
Visualizing the Results of Biclustering and Boolean Matrix Factorization Algo...
This archive contains the code to visualize biclusters from the paper "Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations" by Thibault Marette, Pauli... -
Reducing Graph Structural Bias by Adding shortcut edges
Algorithms that tackle the problem of minimizing average/maximum hitting time (BMAH/BMMH) between different social network groups, given fixed shortcut edges. The...-
Data
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Data
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Visualizing the Results of Boolean Matrix Factorizations
We provide a method to visualize the results of Boolean Matrix Factorization algorithms. Our method can also be used to visualize overlapping clusters in bipartite graphs. The... -
XAI Method for explaining time-series
LASTS is a framework that can explain the decisions of black box models for time series classification. The explanation consists of factual and counterfactual rules revealing... -
Geolet
Geolet is a Python library that offers an interpretable transformation and classification approach for trajectory data. Geolet first partitions trajectories into multiple... -
GLocalX - Explaining in a Local to Global setting
GLocalX is a model-agnostic Local to Global explanation algorithm. Given a set of local explanations expressed in the form of decision rules, and a black-box model to explain,... -
MARLENA
MARLENA is novel technique able to explain the reasons behind any black-box multi-label classifier decision. It will generate an explanation in the form of a decision rule....-
python
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python
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LORE
The recent years have witnessed the rise of accurate but obscure decision systems which hide the logic of their internal decision processes to the users. The lack of...-
python
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python
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Focus Metric
https://github.com/HPAI-BSC/Focus-Metric Implementation of the Focus metric. This metric is able to evaluate explainability methods and quantify their coherency to the task...-
github
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github
