Scalable Spatiotemporal Prediction with Bayesian Neural Fields

Autor: Saad, Feras, Burnim, Jacob, Carroll, Colin, Patton, Brian, Köster, Urs, Saurous, Rif A., Hoffman, Matthew

Publikováno v: Nature Communications 15(7942), 2024

Spatiotemporal datasets, which consist of spatially-referenced time series, are ubiquitous in diverse applications, such as air pollution monitoring, disease tracking, and cloud-demand forecasting. As the scale of modern datasets increases, there is

Externí odkaz: http://arxiv.org/abs/2403.07657

Lightweight Specifications for Parallel Correctness

Autor: Burnim, Jacob Samuels

Publikováno v: Burnim, Jacob Samuels. (2012). Lightweight Specifications for Parallel Correctness. UC Berkeley: Computer Science. Retrieved from: http://www.escholarship.org/uc/item/9vt9p147

With the spread of multicore processors, it is increasingly necessaryfor programmers to write parallel software. Yet writing correctparallel software with explicit multithreading remains a difficultundertaking. Though many tools exist to help test, d

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______325::21f68de49664b8780641e5f12af43f1e
http://www.escholarship.org/uc/item/9vt9p147

CONCURRIT.

Autor: Elmas, Tayfun, Burnim, Jacob, Necula, George, Sen, Koushik

Publikováno v: Proceedings of the 34th ACM SIGPLAN Conference Programming Language Design & Implementation; 6/16/2013, p153-164, 12p

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NDSeq.

Autor: Burnim, Jacob, Elmas, Tayfun, Necula, George, Sen, Koushik

Publikováno v: Proceedings of the 32nd ACM SIGPLAN Conference: Programming Language Design & Implementation; 6/ 4/2011, p401-414, 14p