Researchers have demonstrated a new training technique that significantly improves the accuracy of graph neural networks (GNNs)—AI systems used in applications from drug discovery to weather ...

Graphs are a ubiquitous data structure and a universal language for representing objects and complex interactions. They can model a wide range of real-world systems, such as social networks, chemical ...

For predicting relapse in 1,387 patients with early-stage (I-II) NSCLC from the Spanish Lung Cancer Group data (average age 65.7 years, female 24.8%, male 75.2%), we train tabular and graph machine ...

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 ...

Data science is largely an enigma to the enterprise. Although there’s an array of self-service options to automate its various processes, the actual work performed by data scientists (and how it’s ...