research
∙
07/13/2023
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations
Explainable Artificial Intelligence (XAI) has received widespread intere...
share
research
∙
05/26/2023
GLOBE-CE: A Translation-Based Approach for Global Counterfactual Explanations
Counterfactual explanations have been widely studied in explainability, ...
research
∙
05/19/2023
Robust Counterfactual Explanations for Neural Networks With Probabilistic Guarantees
There is an emerging interest in generating robust counterfactual explan...
research
∙
02/09/2023
Symbolic Metamodels for Interpreting Black-boxes Using Primitive Functions
One approach for interpreting black-box machine learning models is to fi...
research
∙
10/16/2022
CLEAR: Generative Counterfactual Explanations on Graphs
Counterfactual explanations promote explainability in machine learning m...
research
∙
07/06/2022
Robust Counterfactual Explanations for Tree-Based Ensembles
Counterfactual explanations inform ways to achieve a desired outcome fro...
research
∙
04/14/2022
Global Counterfactual Explanations: Investigations, Implementations and Improvements
Counterfactual explanations have been widely studied in explainability, ...
research
∙
10/30/2021
A Survey on the Robustness of Feature Importance and Counterfactual Explanations
There exist several methods that aim to address the crucial task of unde...
research
∙
05/15/2020
Reliable Local Explanations for Machine Listening
One way to analyse the behaviour of machine learning models is through l...
research
∙
04/21/2019
GAN-based Generation and Automatic Selection of Explanations for Neural Networks
One way to interpret trained deep neural networks (DNNs) is by inspectin...
research
∙
05/22/2018
