Results 51 to 60 of about 24,682 (247)
Explainable AI Frameworks: Navigating the Present Challenges and Unveiling Innovative Applications
AlgorithmsThis study delves into the realm of Explainable Artificial Intelligence (XAI) frameworks, aiming to empower researchers and practitioners with a deeper understanding of these tools. We establish a comprehensive knowledge base by classifying and analyzing
Neeraj Anand Sharma +5 more
doaj +1 more source
Explainable Software Bot Contributions: Case Study of Automated Bug Fixes
, 2019 In a software project, esp. in open-source, a contribution is a valuable piece of work made to the project: writing code, reporting bugs, translating, improving documentation, creating graphics, etc.
Monperrus, Martin
core +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
Advanced Intelligent Discovery, EarlyView.This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
Explainable Artificial Intelligence for Resilient Security Applications in the Internet of Things
IEEE Open Journal of the Communications SocietyThe performance of Artificial Intelligence (AI) systems reaches or even exceeds that of humans in an increasing number of complicated tasks. Highly effective non-linear AI models are generally employed in a black-box form nested in their complex ...
Mohammed Tanvir Masud +4 more
doaj +1 more source
Ameliorating Algorithmic Bias, or Why Explainable AI Needs Feminist Philosophy
Feminist Philosophy Quarterly, 2022 Artificial intelligence (AI) systems are increasingly adopted to make decisions in domains such as business, education, health care, and criminal justice.
Linus Ta-Lun Huang +4 more
doaj
Explainable Artificial Intelligence (XAI) in Healthcare
, 2023 Artificial Intelligence (AI) describes computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. Examples of AI techniques are machine learning, neural networks and deep learning.
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
, 2019 In today's legal environment, lawsuits and regulatory investigations require companies to embark upon increasingly intensive data-focused engagements to identify, collect and analyze large quantities of data.
Chhatwal, Rishi +5 more
core +1 more source
The Tower of Babel in Explainable Artificial Intelligence (XAI)
, 2023 AbstractAs machine learning (ML) has emerged as the predominant technological paradigm for artificial intelligence (AI), complex black box models such as GPT-4 have gained widespread adoption. Concurrently, explainable AI (XAI) has risen in significance as a counterbalancing force.
David Schneeberger +6 more
openaire +1 more source
Advanced Intelligent Discovery, EarlyView.Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source