Discrete Global Grid Systems (DGGS) have emerged as a robust framework for organising and analysing geospatial data across the entire Earth. By partitioning the globe into a hierarchy of optimally ...

Researchers at Los Alamos National Laboratory have developed a new approach that addresses the limitations of generative AI models. Unlike generative diffusion models, the team's Discrete Spatial ...

At each sampling time instant, one observes system output and action to form discrete-time rewards. The sampled input-output data are collected along the trajectory of the dynamical system in ...

In political science, data with heterogeneous units are used in many studies, such as those involving legislative proposals in different policy areas, electoral choices by different types of voters, ...

[video:https://www.youtube.com/watch?v=nYl0ss1oJAE&feature=emb_imp_woyt] In a world where decisions of all kinds are based on information derived from large datasets ...

When doing my research for this column I often come across discussion about the size of a fund and how bigger is not necessarily better. Let us just stop and think about that. Some fund managers argue ...

Importing, transforming, and validating data from unmanaged external sources is a messy, complex process. A data exchange platform can help. What has always fascinated me about Moore’s law is that for ...

When generative artificial intelligence (genAI) burst into prominence with the release of ChatGPT in 2022, technically savvy business users quickly began experimenting. At that time, existing tools ...

Electronic health record (EHR) adoption was driven, in part, by a recognition of the power of data. Given the complexities of healthcare informatics, though, the full potential of health data has been ...