These short anomaly-detection puzzles are designed to illustrate how reasoning often depends on identifying inconsistencies ...
Materials scientists at Rice University have developed a new workflow methodology for measuring microscopic defects in ...
EVENTTSF: Event-Aware Non-Stationary Time Series Forecasting Code IJCAI 2026 SeesawNet: Towards Non-stationary Time Series Forecasting with Balanced Modeling of Common and Specific Dependencies Code ...
State Key Laboratory of Blockchain and Data Security, Zhejiang University, Hangzhou, China Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security, Hangzhou, China Aerial ...
🔍 A comprehensive collection of papers, datasets, and tools for AI-Generated Content (AIGC) detection research. This repository tracks research on detecting AI-generated content across image, video, ...
Activation Function,Anomaly Detection,Bearing Fault Diagnosis,Complex Defects,Convolutional Neural Network,F1 Score,Fault Diagnosis,Fault Modes,Frequency Domain,High ...
This article is not about ethics, privacy, security, ownership, or corporate governance — I am going to circumvent all of this here by using some made-up data relating to supermarket sales: Here, I ...
This study investigates whether anomaly-aware modeling can improve stock price forecasting by incorporating signals that highlight unusual market behavior. Financial time series often contain sudden ...
The proliferation of digital platforms has enabled fraudsters to deploy sophisticated camouflage techniques, such as multi-hop collaborative attacks, to evade detection. Traditional Graph Neural ...
Laboratoire de Matériaux et Environnement (LAME), Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso. In recent decades, the impact of climate change on natural resources has increased. However, ...
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