In a recent analysis, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and collaborator William Gilpin reported that one ...

Dive into the concept of Local Response Normalization (LRN) in deep learning. This video breaks down its role in neural networks and how it helps improve model performance.

A new study in Small introduces OptiMate, a machine learning model that predicts optical properties and identifies ...

Machine learning and artificial intelligence are fundamentally dependent on databases. These databases serve the vital role of storing, organizing, and pulling up necessary data to develop and ...

Machine learning models are becoming increasingly important in the ... This paper introduces surrogate data models as dimensionality reduction tools in large-scale crisis prediction models. The ...

Found in knee replacements and bone plates, aircraft components, and catalytic converters, the exceptionally strong metals known as multiple principal element alloys (MPEA) are about to get even ...

Machine learning (ML) involves rote mathematical or mechanical processes only. Artificial intelligence then advances data science and machine learning even further. Ben Tasker “(Machine learning uses) ...

Endogenous intracellular allosteric modulators of GPCRs remain largely unexplored, with limited binding and phenotype data available. This gap arises from the lack of robust computational methods for ...