[HTML][HTML] Notions of explainability and evaluation approaches for explainable artificial intelligence
Abstract Explainable Artificial Intelligence (XAI) has experienced a significant growth over
the last few years. This is due to the widespread application of machine learning, particularly …
the last few years. This is due to the widespread application of machine learning, particularly …
[HTML][HTML] Explainable machine learning in materials science
Abstract Machine learning models are increasingly used in materials studies because of
their exceptional accuracy. However, the most accurate machine learning models are …
their exceptional accuracy. However, the most accurate machine learning models are …
[HTML][HTML] Explainable Artificial Intelligence (XAI): What we know and what is left to attain Trustworthy Artificial Intelligence
Artificial intelligence (AI) is currently being utilized in a wide range of sophisticated
applications, but the outcomes of many AI models are challenging to comprehend and trust …
applications, but the outcomes of many AI models are challenging to comprehend and trust …
[HTML][HTML] Exploring the challenges of remote work on Twitter users' sentiments: From digital technology development to a post-pandemic era
JR Saura, D Ribeiro-Soriano, PZ Saldaña - Journal of Business Research, 2022 - Elsevier
The boost in the use and development of technology, spurred by COVID-19 pandemic and
its consequences, has sped up the adoption of new technologies and digital platforms in …
its consequences, has sped up the adoption of new technologies and digital platforms in …
Explaining anomalies detected by autoencoders using Shapley Additive Explanations
Deep learning algorithms for anomaly detection, such as autoencoders, point out the
outliers, saving experts the time-consuming task of examining normal cases in order to find …
outliers, saving experts the time-consuming task of examining normal cases in order to find …
Explainable deep learning: A field guide for the uninitiated
Deep neural networks (DNNs) are an indispensable machine learning tool despite the
difficulty of diagnosing what aspects of a model's input drive its decisions. In countless real …
difficulty of diagnosing what aspects of a model's input drive its decisions. In countless real …
Explainable artificial intelligence: a systematic review
Explainable Artificial Intelligence (XAI) has experienced a significant growth over the last few
years. This is due to the widespread application of machine learning, particularly deep …
years. This is due to the widespread application of machine learning, particularly deep …
The importance of interpretability and visualization in machine learning for applications in medicine and health care
A Vellido - Neural computing and applications, 2020 - Springer
In a short period of time, many areas of science have made a sharp transition towards data-
dependent methods. In some cases, this process has been enabled by simultaneous …
dependent methods. In some cases, this process has been enabled by simultaneous …
[HTML][HTML] A survey of visual analytics techniques for machine learning
Visual analytics for machine learning has recently evolved as one of the most exciting areas
in the field of visualization. To better identify which research topics are promising and to …
in the field of visualization. To better identify which research topics are promising and to …
Visual analytics in deep learning: An interrogative survey for the next frontiers
Deep learning has recently seen rapid development and received significant attention due
to its state-of-the-art performance on previously-thought hard problems. However, because …
to its state-of-the-art performance on previously-thought hard problems. However, because …