Tech Xplore on MSN

HarmonyGNN boosts graph AI accuracy on four tough benchmarks by up to 9.6%

Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks ...
Phys.org

Novel graph neural network models enhance precipitation forecasting

In the AI era, pure data-driven meteorological and climate models are gradually catching up with and even surpassing traditional numerical models. However, significant challenges persist in current ...
SiliconANGLE

Google’s new GraphCast AI model can forecast the weather 10 days in advance

Google LLC today detailed a new artificial intelligence model, GraphCast, that it says can generate weather forecasts faster and more accurately than traditional algorithms. The neural network was ...
Risk

Stock trend forecasting with graph neural networks

Accurate stock trend forecasting is a central challenge in financial economics due to the highly nonlinear and interdependent nature of market dynamics. Traditional statistical and machine learning ...
EurekAlert!

Dynamic traveling time forecasting based on spatial-temporal graph convolutional networks

Traveling time forecasting, the core component in GPS navigation systems and taxi-hailing apps, has attracted widespread attention. Existing research mostly focuses on independent points like traffic ...
KXAN

GraphCast: Is AI weather model the forecasting future?

AUSTIN (KXAN) — Google entered the field of weather forecasting with the debut of their GraphCast AI weather computer model. KXAN Meteorologist Nick Bannin spoke with UT Austin Professor Liang Yang ...
EurekAlert!

Integrating physics and AI: Novel graph neural network models enhance precipitation forecasting

In the AI era, pure data-driven meteorological and climate models are gradually catching up with, and even surpassing, traditional numerical models. However, significant challenges persist in current ...