Enormous amounts of data are being produced everyday by sub-meters and smart sensors
installed in residential buildings. If leveraged properly, that data could assist end-users …

Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by
enhancing the trust of end-users in machines. As the number of connected devices keeps on …

In the past two decades, most research on anomaly detection has focused on improving the
accuracy of the detection, while largely ignoring the explainability of the corresponding …

Deep learning (DL), a branch of machine learning (ML), is the core technology in today's
technological advancements and innovations. Deep learning-based approaches are the …

With the extensive application of deep learning (DL) algorithms in recent years, eg, for
detecting Android malware or vulnerable source code, artificial intelligence (AI) and …

Artificial Intelligence (AI) is becoming fundamental in almost all activity sectors in our society.
However, most of the modern AI techniques (eg, Machine Learning–ML) have a black box …

Abstract Space anomaly detection plays a critical role in safeguarding the integrity and
reliability of space systems amid the rising tide of threats. This survey aims to deepen …

External stakeholders require accurate and explainable financial distress prediction (FDP)
models. Complex machine learning algorithms offer high accuracy, but most of them lack …

Abstract Explainable Artificial Intelligence refers to develo** artificial intelligence models
and systems that can provide clear, understandable, and transparent explanations for their …

Explainable Artificial Intelligence (XAI) aims to improve the transparency of machine
learning (ML) pipelines. We systematize the increasingly growing (but fragmented) …