These short anomaly-detection puzzles are designed to illustrate how reasoning often depends on identifying inconsistencies ...
Large language model agents increasingly maintain persistent state through memory files, tool configurations, and long-term identity documents. Systems such as Cursor, AutoGPT, and Claude Code read ...
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 ...
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, ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. This study investigates fault diagnosis, encompassing fault detection, isolation, and ...
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