Results 201 to 210 of about 22,315 (263)
Gated attention based generative adversarial networks for imbalanced credit card fraud detection. [PDF]
Ge J, Yin L, Zhang S, Zhao X.
europepmc +1 more source
This publication describes how R. B. Woodward and Roald Hoffmann crafted their masterpiece publications. Illustrations include Woodward's first draft of the famous “Violations There are none. Nor can violations be expected of so fundamental a principle of maximum bonding.” Original but discarded text shows the stepwise paths toward the W‐H masterpieces.
Jeffrey I. Seeman
wiley +1 more source
Reinforcement learning with graph neural network (RL-GNN) fusion for real-time financial fraud detection: a context-aware community mining approach. [PDF]
Devi RR, Raja JE, Chin YB.
europepmc +1 more source
DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection
Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +1 more source
Graph convolution network for fraud detection in bitcoin transactions. [PDF]
Asiri A, Somasundaram K.
europepmc +1 more source
ABSTRACT Small and medium‐sized enterprises (SMEs) face significant institutional barriers when expanding across borders, including regulatory constraints, financial accessibility issues, and market entry challenges. Institutional theory provides a useful framework for understanding how external regulative, normative, and cognitive institutional forces
Sharmin Nahar, Muntasir Alam
wiley +1 more source
Enhancing fraud detection in the Ethereum blockchain using ensemble learning. [PDF]
Gu Z, Dib O.
europepmc +1 more source
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha +9 more
wiley +1 more source
Innovative novel regularized memory graph attention capsule network for financial fraud detection. [PDF]
Shi X +5 more
europepmc +1 more source

