Machine learning algorithms have been used to predict cancer progression, identify early signs of Parkinson’s disease, and ...

PCA is an important tool for dimensionality reduction in data science and to compute grasp poses for robotic manipulation from point cloud data. PCA can also directly used within a larger machine ...

A research team has unveiled a non-destructive, highly accurate approach for determining the optimal timing of embryo rescue ...

Functional principal component analysis (FPCA) is a popular approach to explore major sources of variation in a sample of random curves. These major sources of variation are represented by functional ...

This manuscript considers regression models for generalized, multilevel functional responses: functions are generalized in that they follow an exponential family distribution and multilevel in that ...

In recent years, the integration of machine learning and robotics technologies in chemical analysis has transformed the landscape of scientific research and industry practices. This revolution is not ...

Machine learning model provides quick method for determining the composition of solid chemical mixtures using only photographs of the sample. Machine learning model provides quick method for ...