These systems focus on improving forecast accuracy, efficiency, and extreme weather handling through advanced machine learning architectures.

Accurate and efficient traffic speed prediction is crucial for improving road safety and efficiency. With the emerging deep ...

CGSchNet, a fast machine-learned model, simulates proteins with high accuracy, enabling drug discovery and protein ...

Model for predicting molecular crystal properties is readily adaptable to specific tasks, even with limited data ...

Drug discovery has long been criticized for its slow, costly, and failure-prone nature. Traditional approaches, particularly ...

Probability and Statistics Group research at the School of Mathematical and Computer Sciences at Heriot-Watt University, Edinburgh.

Powered by differentiable imaging, Uncertainty - Aware Fourier Ptychography (UA - FP) revolutionizes computational imaging.

Machine learning helps improve accuracy and efficiency of small-molecule calculations Microsoft researchers used deep learning to create new DFT model by Sam Lemonick, special to C&EN June 20, 2025 ...

In this work, we present Skala, a modern deep learning-based XC functional that bypasses expensive hand-designed features by learning representations directly from data. Skala achieves chemical ...

Microsoft researchers achieved a breakthrough in the accuracy of DFT, a method for predicting the properties of molecules and materials, by using deep learning. This work can lead to better batteries, ...