A comprehensive taxonomy for explainable artificial intelligence: a systematic survey of surveys on methods and concepts
G Schwalbe, B Finzel - Data Mining and Knowledge Discovery, 2024 - Springer
In the meantime, a wide variety of terminologies, motivations, approaches, and evaluation
criteria have been developed within the research field of explainable artificial intelligence …
criteria have been developed within the research field of explainable artificial intelligence …
Adversarial attacks and defenses in explainable artificial intelligence: A survey
H Baniecki, P Biecek - Information Fusion, 2024 - Elsevier
Explainable artificial intelligence (XAI) methods are portrayed as a remedy for debugging
and trusting statistical and deep learning models, as well as interpreting their predictions …
and trusting statistical and deep learning models, as well as interpreting their predictions …
Dalex: responsible machine learning with interactive explainability and fairness in python
H Baniecki, W Kretowicz, P PiÄ, J WiĹ - Journal of Machine Learning …, 2021 - jmlr.org
In modern machine learning, we observe the phenomenon of opaqueness debt, which
manifests itself by an increased risk of discrimination, lack of reproducibility, and deated …
manifests itself by an increased risk of discrimination, lack of reproducibility, and deated …
Explainable and interpretable machine learning and data mining
The growing number of applications of machine learning and data mining in many domains—
from agriculture to business, education, industrial manufacturing, and medicine—gave rise …
from agriculture to business, education, industrial manufacturing, and medicine—gave rise …
survex: an R package for explaining machine learning survival models
Due to their flexibility and superior performance, machine learning models frequently
complement and outperform traditional statistical survival models. However, their …
complement and outperform traditional statistical survival models. However, their …
shapiq: Shapley interactions for machine learning
Originally rooted in game theory, the Shapley Value (SV) has recently become an important
tool in machine learning research. Perhaps most notably, it is used for feature attribution and …
tool in machine learning research. Perhaps most notably, it is used for feature attribution and …
Explanation as a process: user-centric construction of multi-level and multi-modal explanations
In the last years, XAI research has mainly been concerned with developing new technical
approaches to explain deep learning models. Just recent research has started to …
approaches to explain deep learning models. Just recent research has started to …
Exploration of Rashomon set assists explanations for medical data
K Kobylińska, M Krzyziński, R Machowicz… - arXiv preprint arXiv …, 2023 - arxiv.org
The machine learning modeling process conventionally culminates in selecting a single
model that maximizes a selected performance metric. However, this approach leads to …
model that maximizes a selected performance metric. However, this approach leads to …
Explainable artificial intelligence based fault diagnosis and insight harvesting for steel plates manufacturing
A Kharal - arXiv preprint arXiv:2008.04448, 2020 - arxiv.org
With the advent of Industry 4.0, Data Science and Explainable Artificial Intelligence (XAI) has
received considerable intrest in recent literature. However, the entry threshold into XAI, in …
received considerable intrest in recent literature. However, the entry threshold into XAI, in …
Explain to Question not to Justify
Explainable Artificial Intelligence (XAI) is a young but very promising field of research.
Unfortunately, the progress in this field is currently slowed down by divergent and …
Unfortunately, the progress in this field is currently slowed down by divergent and …