A new framework integrates graph databases with real-time machine learning to enhance fraud detection and risk control in digital finance. By ...

Platforms like Stats Edge and GRID Insights have made such systems commercially viable, combining player and team data, projection engines, real-time match tracking, and predictive features. GRID ...

Traditional EDA tools rely on heuristics and static algorithms, which struggle to scale with modern design complexity. AI introduces a data-driven, adaptive approach, capable of learning from vast ...

Abstract: Accurate short-term predictions of active mode traffic are crucial for effective urban traffic control and management, helping to reduce delays, stops, and improve travel time reliability, ...

Yann LeCun has become mainstream during the recent AI revolution in his role as the Chief AI Scientist at Meta, but he’s ...

Machine learning has become the critical enabler for addressing these challenges. Traditional ML models, including random ...

Artificial intelligence is revolutionising quantitative finance, enabling smarter trading through advanced models, feature ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...

Abstract: By focusing on the structure exploration and information propagation from non-Euclidean data space, graph convolutional neural network (GCN), which can extract abundant and discriminative ...

State Key Laboratory of Integrated Service Networks, Xidian University, Xian 710071, China State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology School of Microelectronics, Xidian ...