The interdisciplinary field of explainable artificial intelligence (XAI) aims to foster human understanding of black-box machine learning models through explanation methods …
Thanks to the exponential growth in computing power and vast amounts of data, artificial intelligence (AI) has witnessed remarkable developments in recent years, enabling it to be …
Understanding black box models has become paramount as systems based on opaque Artificial Intelligence (AI) continue to flourish in diverse real-world applications. In response …
The continuous advancement of Artificial Intelligence (AI) has been revolutionizing the strategy of decision-making in different life domains. Regardless of this achievement, AI …
The rising popularity of explainable artificial intelligence (XAI) to understand high-performing black boxes raised the question of how to evaluate explanations of machine learning (ML) …
In the last few years, Artificial Intelligence (AI) has achieved a notable momentum that, if harnessed appropriately, may deliver the best of expectations over many application sectors …
A Das, P Rad - arXiv preprint arXiv:2006.11371, 2020 - arxiv.org
Nowadays, deep neural networks are widely used in mission critical systems such as healthcare, self-driving vehicles, and military which have direct impact on human lives …
V Shah, SR Konda - INTERNATIONAL JOURNAL OF …, 2021 - researchgate.net
In this paper, we explore the intersection of neural networks and explainable artificial intelligence (XAI), aiming to bridge the gap between complex model architectures and …
The main objective of eXplainable Artificial Intelligence (XAI) is to provide effective explanations for black-box classifiers. The existing literature lists many desirable properties …