[HTML][HTML] Knowledge graphs as tools for explainable machine learning: A survey
This paper provides an extensive overview of the use of knowledge graphs in the context of
Explainable Machine Learning. As of late, explainable AI has become a very active field of …
Explainable Machine Learning. As of late, explainable AI has become a very active field of …
[PDF][PDF] Semantic web technologies for explainable machine learning models: A literature review.
Due to their tremendous potential in predictive tasks, Machine Learning techniques such as
Artificial Neural Networks have received great attention from both research and practice …
Artificial Neural Networks have received great attention from both research and practice …
Explainable image classification: The journey so far and the road ahead
Explainable Artificial Intelligence (XAI) has emerged as a crucial research area to address
the interpretability challenges posed by complex machine learning models. In this survey …
the interpretability challenges posed by complex machine learning models. In this survey …
Survey on ontology-based explainable AI in manufacturing
Artificial intelligence (AI) has become an essential tool for manufacturers seeking to optimize
their production processes, reduce costs, and improve product quality. However, the …
their production processes, reduce costs, and improve product quality. However, the …
Semantic referee: A neural-symbolic framework for enhancing geospatial semantic segmentation
Understanding why machine learning algorithms may fail is usually the task of the human
expert that uses domain knowledge and contextual information to discover systematic …
expert that uses domain knowledge and contextual information to discover systematic …
[PDF][PDF] Conceptual Edits as Counterfactual Explanations.
We propose a framework for generating counterfactual explanations of black-box classifiers,
which answer the question “What has to change for this to be classified as X instead of Y?” …
which answer the question “What has to change for this to be classified as X instead of Y?” …
Searching for explanations of black-box classifiers in the space of semantic queries
Deep learning models have achieved impressive performance in various tasks, but they are
usually opaque with regards to their inner complex operation, obfuscating the reasons for …
usually opaque with regards to their inner complex operation, obfuscating the reasons for …
Computing rule-based explanations of machine learning classifiers using knowledge graphs
E Dervakos, O Menis-Mastromichalakis… - ar** from aerial imagery improve nitrous oxide emissions estimates from grazed grassland?
Most nitrogen (N) lost to the environment from grazed grassland is produced as a result of N
excreted by livestock, released in the form of nitrous oxide (N2O) emissions, nitrate leaching …
excreted by livestock, released in the form of nitrous oxide (N2O) emissions, nitrate leaching …