Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of agricultural watersheds. To address this need, a team of researchers led by the ...

The unprecedented explosion in the amount of information we are generating and collecting, thanks to the arrival of the internet and the always-online society, powers all the incredible advances we ...

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

Spatially distributed prediction of streamflow and nitrogen (N) export dynamics is essential for precision management of ...

Giulia Livieri sets out remarkable new research with results that clarify how learning works on complex graphs and how quickly any method (including Graph Convolutional Networks) can learn from them, ...

Cyber threats are increasing in speed and complexity, driving the need for advanced detection techniques. Machine learning is ...

The multiple condition (MC)-retention model is an uncertainty-aware graph-based neural network that predicts liquid chromatography (LC) retention times across multiple column chem ...