Budoen, A. , Zhang, M. and Jr., L. (2025) A Comparative Study of Ensemble Learning Techniques and Classification Models to Identify Phishing Websites. Open Access Library Journal, 12, 1-22. doi: ...

Hallucination is one of the most researched topics in AI. Recent studies show we’ve got it all wrong, writes Satyen K.

Rose Yu has drawn on the principles of fluid dynamics to improve deep learning systems that predict traffic, model the ...

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions ...

Rigorous study design and analytical standards are required to generate reliable findings in healthcare from artificial intelligence (AI) research. One crucial but often overlooked aspect is the ...

GA4 attribution models don’t just report results — they influence them. See how model choice impacts marketing strategy, spend and perceived ROI. The post A guide to attribution models in GA4 appeared ...

This useful manuscript describes cryo-EM structures of archaeal proteasomes that reveal insights into how occupancy of binding pockets on the 20S protease regulates proteasome gating. The evidence ...

Abstract: This article proposes the operating status prediction model at electric vehicle (EV) charging stations based on the spatiotemporal graph convolutional network (SGCN). The SGCN combines graph ...

This repository offers tools for detecting DeepFakes using a hybrid CNN–LSTM model. Explore the code to train and evaluate on popular datasets like DFDC and AvLips. 🐙 ...

The graphs show 99 possible scenarios (grey lines), that are produced by the Bureau's climate long-range forecast model, which represent the range of outcomes that may occur over the forecast period.

Anomaly detection in transactions means identifying unusual or unexpected patterns within transactions or related activities. These patterns, known as anomalies or outliers, deviate significantly from ...