In the last decade, machine learning evolved from a sub-field of computer science into one of the most impactful scientific disciplines of our time. While this has brought impressive scientific advances, there are now increasing concerns about the applications of artificial intelligence systems in societal contexts. Many concerns are rooted in the fact that machine learning models can be incredibly opaque. To overcome this problem, the nascent field of explainable machine learning attempts to provide human-understandable explanations for the behavior of complex models. After an initial period of method development and excitement, researchers in this field have now recognized the many difficulties inherent in faithfully explaining complex mo...
As machine learning is increasingly deployed in high-stakes contexts affecting people's livelihoods,...
Machine intelligence and data science are two disciplines that are attempting to develop Artificial ...
International audienceThis book compiles leading research on the development of explainable and inte...
Machine learning-based systems are now part of a wide array of real-world applications seamlessly em...
Machine learning-based systems are now part of a wide array of real-world applications seamlessly em...
Despite AI and Neural Networks model had an overwhelming evolution during the past decade, their app...
Machine Learning Explainability: Exploring Automated Decision-Making Through Transparent Modelling a...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
eXplainable AI focuses on generating explanations for the output of an AI algorithm to a user, usual...
Explainable artificial intelligence and interpretable machine learning are research fields growing i...
This dissertation seeks to clarify and resolve a number of fundamental issues surrounding algorithmi...
Explainability in Artificial Intelligence (AI) has been revived as a topic of active research by the...
The most effective Artificial Intelligence (AI) systems exploit complex machine learning models to f...
67 pages, 13 figures, under review in the Information Fusion journalIn the last years, Artificial In...
As machine learning is increasingly deployed in high-stakes contexts affecting people's livelihoods,...
Machine intelligence and data science are two disciplines that are attempting to develop Artificial ...
International audienceThis book compiles leading research on the development of explainable and inte...
Machine learning-based systems are now part of a wide array of real-world applications seamlessly em...
Machine learning-based systems are now part of a wide array of real-world applications seamlessly em...
Despite AI and Neural Networks model had an overwhelming evolution during the past decade, their app...
Machine Learning Explainability: Exploring Automated Decision-Making Through Transparent Modelling a...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
Recent work on interpretability in machine learning and AI has focused on the building of simplified...
eXplainable AI focuses on generating explanations for the output of an AI algorithm to a user, usual...
Explainable artificial intelligence and interpretable machine learning are research fields growing i...
This dissertation seeks to clarify and resolve a number of fundamental issues surrounding algorithmi...
Explainability in Artificial Intelligence (AI) has been revived as a topic of active research by the...
The most effective Artificial Intelligence (AI) systems exploit complex machine learning models to f...
67 pages, 13 figures, under review in the Information Fusion journalIn the last years, Artificial In...
As machine learning is increasingly deployed in high-stakes contexts affecting people's livelihoods,...
Machine intelligence and data science are two disciplines that are attempting to develop Artificial ...
International audienceThis book compiles leading research on the development of explainable and inte...