Researchers developed a hybrid UMAP-HDBSCAN-SVM machine learning workflow to rapidly classify low-loss STEM-EELS spectrum ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

After decades of frustration, machine-learning tools are unlocking a treasure trove of acoustic data for ecologists. A small songbird soars above Ithaca, New York, on a September night. He is one of 4 ...

However, by the late 1970s, there was disappointment that the two main approaches to computing in medicine — rule-based systems and matching, or pattern recognition, systems — had not been as ...

Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests. Systems controlled by next-generation computing ...