Scientific Research Publishing

Deep Reinforcement Learning for Phishing Detection with Transformer-Based Semantic Features ()

Phishing is a form of cybercrime in which people are deceived into exposing their personal information which can result in ...
Mint

Who Is Andrej Karpathy? The AI researcher behind Tesla Autopilot, OpenAI and the course that taught millions

Few people have shaped modern artificial intelligence across as many dimensions as Andrej Karpathy, as a researcher, engineer and teacher. Over the past decade, he has been at the forefront of some of ...
IEEE

TransforLearn: Interactive Visual Tutorial for the Transformer Model

Abstract: The widespread adoption of Transformers in deep learning, serving as the core framework for numerous large-scale language models, has sparked significant interest in understanding their ...
GitHub

Deep learning for time series forecasting, classification, and anomaly detection

Flow Forecast (FF) is an open-source deep learning for time series forecasting framework. It provides all the latest state of the art models (transformers, attention models, GRUs, ODEs) and cutting ...
Scientific Research Publishing

GNSS-R Soil Moisture Retrieval Method Based on Transformer Fusion Network ()

Global Navigation Satellite System-Reflectometry (GNSS-R) remote sensing technology, with its advantages of low cost, short revisit cycle, and high-precision positioning, has been widely applied in ...
Nature

Transformers for rapid detection of airway stenosis and stridor

Upper airway stenosis is a potentially life-threatening condition involving the narrowing of the airway. In more severe cases, airway stenosis may be accompanied by stridor, a type of disordered ...
Frontiers

Transformer-based short-term traffic forecasting model considering traffic spatiotemporal correlation

Traffic forecasting is crucial for a variety of applications, including route optimization, signal management, and travel time estimation. However, many existing prediction models struggle to ...