Latest from Google AI – SimPer: Simple self-supervised learning of periodic targets
Posted by Daniel McDuff, Staff Research Scientist, and Yuzhe Yang, Student Researcher, Google Learning from periodic data (signals that repeat, such as a heart beat or the daily temperature changes on Earth’s surface) is crucial for many real-world applications, from monitoring weather systems to detecting vital signs. For example, in the environmental remote sensing domain,…
