In this paper we describe an interdisciplinary collaboration between researchers in machine learning and oceanography. The collaboration was formed to study the problem of open oc...
Joshua M. Lewis, Pincelli M. Hull, Kilian Q. Weinb...
This paper presents a multiagent architecture constructed for learning from the interaction between the atmosphere and the ocean. The ocean surface and the atmosphere exchange carb...
This paper considers the elements and challenges of heterogeneous data management and interdisciplinary collaboration, drawing from the literatures on participatory design, comput...
Karen S. Baker, Steven J. Jackson, Jerome R. Wanet...
Error Subspace Statistical Estimation (ESSE), an uncertainty prediction and data assimilation methodology employed for real-time ocean forecasts, is based on a characterization an...
Constantinos Evangelinos, Pierre F. J. Lermusiaux,...
Science is becoming data-intensive, requiring new software architectures that can exploit resources at all scales: local GPUs for interactive visualization, server-side multi-core ...
Keith Grochow, Bill Howe, Mark Stoermer, Roger S. ...