The Potential of Energy-Based RBM and xLSTM for Real-Time Predictive Analytics in Credit Card Fraud Detection

ISSN Print: 2327-7211
ISSN Online: 2327-7203
www.scirp.net/journal/jdaip
E-mail: [email protected]

Citations

"The Potential of Energy-Based RBM and xLSTM for Real-Time Predictive Analytics in Credit Card Fraud Detection"
written by Peyman Baghdadi, Serdar Korukoglu, Mehmet Ali Bilici, Aytug Onan,
published by Journal of Data Analysis and Information Processing, Vol.13 No.1, 2025

has been cited by the following article(s):

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[1]	AI and Financial Fraud Prevention: Mapping the Trends and Challenges Through a Bibliometric Lens Journal of Risk and Financial Management, 2025 DOI:10.3390/jrfm18060323

[2]	Advancing Fraud Detection in Financial Transactions Through AI: Emerging Challenges and Strategic Opportunities 2025 IEEE 5th International Conference on ICT in Business Industry & Government (ICTBIG), 2025 DOI:10.1109/ICTBIG68706.2025.11323726