A probabilistic machine learning-based framework for recognizing and predicting microbial landscape patterns at nested spatial scales was developed. The approach substantially increased the ...

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...

For humans and machines, intelligence requires making sense of the world — inferring simple explanations for the mishmosh of information coming in through our senses, discovering regularities and ...

Edge devices operating in dynamic environments critically need the ability to continually learn without catastrophic forgetting. The strict resource constraints in these devices pose a major challenge ...

A Michigan Tech-developed machine learning model uses probability to more accurately classify breast cancer shown in histopathology images and evaluate the uncertainty of its predictions. Breast ...

When severe weather is brewing and life-threatening hazards like heavy rain, hail or tornadoes are possible, advance warning and accurate predictions are of utmost importance. Weather researchers have ...