With statistical sampling, counsel can simplify damage analyses, avoid potential issues with incomplete or missing data, and minimize the risk of error. In our prior ...

This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...

Abstract: Finite time-vertex graph signals (FTVGS) provide an efficient representation for capturing spatio-temporal correlations across multiple data sources on irregular structures. Although ...

Abstract: Remote sensing change detection (RSCD) aims to identify the regions of interest that have changed between dual-temporal images. However, most deep models predict CD results by extracting ...

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More A new paper by researchers from Google Research and the University of ...

QUARRYVILLE, Pa. — As cases of the avian flu continue to spread, the federal government is calling on dairy farms to provide milk samples to test for the disease. Under the new federal order, dairy ...

As genetic studies grow, researchers are increasingly seeking to identify rare genetic variants with large impacts on traits. In this paper, we combine theoretical methods and data analysis to show ...

SSRS conducted the National Public Opinion Reference Survey (NPORS) for Pew Research Center using address-based sampling and a multimode protocol. The survey was fielded from Feb. 1, 2024, to June 10, ...

A weighted random item sampler (selector), where the probability of selecting an item is proportional to its weight, and every item is sampled exactly once (without repetition or replacement). The ...

A behind-the-scenes blog about research methods at Pew Research Center. For our latest findings, visit pewresearch.org. We’re in the thick of election season and political polls are everywhere, with ...