Design of experiments (DOE) is an established method to allocate resources for efficient parameter space exploration. Model based active learning (AL) data sampling strategies have shown potential for ...

An AI–DFT workflow showing data processing, feature engineering, and model selection integrated with first-principles validation to enable closed-loop materials discovery and design. Credit must be ...

While the model is often the first suspect for AI pilots stalling, the architecture is the more likely culprit.

What if you could take the most tedious, time-consuming tasks in your workflow and have them completed with precision and speed—without lifting a finger? Imagine automating everything from analyzing ...

The identification of optimal candidate genes from large-scale blood transcriptomic data is crucial for developing targeted assays to monitor immune responses. Here, we introduce a novel, optimized ...