Results 141 to 150 of about 56,159 (288)
, 2019 Many of the successful modern machine learning approaches can be described as ``black box'' systems; these systems perform well, but are unable to explain the reasoning behind their decisions. The emerging sub-field of Explainable Artificial Intelligence (XAI) aims to create systems that are able to explain to their users why they made a particular ...
Steging, Cor +2 more
openaire +1 more source
Systematic Review of XAI Tools for AI-HCI Research [PDF]
Ahmad Alaqsam, Corina Sas
openalex +1 more source
Building Quantifiable System for Xai Models
, 2022 Pratyush Rokade, Kumar Raju Alluri BKSP
openalex +1 more source
Validating Explainer Methods: A Functionally Grounded Approach for Numerical Forecasting
Journal of Forecasting, Volume 45, Issue 2, Page 819-836, March 2026.ABSTRACT Forecasting systems have a long tradition in providing outputs accompanied by explanations. While the vast majority of such explanations relies on inherently interpretable linear statistical models, research has put forth eXplainable Artificial Intelligence (XAI) methods to improve the comprehensibility of nonlinear machine learning models. As
Felix Haag +2 more
wiley +1 more source
Explainable Artificial Intelligence (XAI) for 6G: Improving Trust between Human and Machine [PDF]
, 2019 Weisi Guo
openalex +1 more source
Explainable AI (XAI) in Rules as Code (RaC): The DataLex approach
, 2022 Andrew Mowbray +2 more
openalex +1 more source
Edge‐Oriented DoS/DDoS Intrusion Detection and Supervision Platform
SECURITY AND PRIVACY, Volume 9, Issue 2, March/April 2026.ABSTRACT This work presents an Edge Node‐Oriented DoS/DDoS Intrusion Detection and Monitoring Platform, a novel anomaly detection system based on temporal analysis with machine learning (ML) and deep learning (DL) algorithms, specifically designed to operate on edge servers with limited resources.
Geraldo Eufrazio Martins Júnior +3 more
wiley +1 more source
Counterfactual Explanations in Education: A Systematic Review
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 1, March 2026.Main challenges on counterfactual explanations in education. ABSTRACT Counterfactuals are a type of explanations based on hypothetical scenarios used in Explainable Artificial Intelligence (XAI), showing what changes in input variables could have led to different outcomes in predictive problems.
Pamela Buñay‐Guisñan +2 more
wiley +1 more source
International Journal of Language &Communication Disorders, Volume 61, Issue 2, March/April 2026.ABSTRACT Background Artificial Intelligence (AI) is increasingly discussed as a tool that can support speech and language therapy (SLT). However, clinical adoption of AI requires improved AI literacy among clinicians. AI is a rapidly evolving and often inconsistently defined field that can be difficult to navigate.
Ana Oliveira‐Buckley +3 more
wiley +1 more source
Expert Systems, Volume 43, Issue 3, March 2026.ABSTRACT Zero‐day exploits remain challenging to detect because they often appear in unknown distributions of signatures and rules. The article entails a systematic review and cross‐sectional synthesis of four fundamental model families for identifying zero‐day intrusions, namely, convolutional neural networks (CNN), deep neural networks (DNN ...
Abdullah Al Siam +3 more
wiley +1 more source