Skip to main content
U.S. flag

An official website of the United States government

Conference Papers

Browse almost 5,000 conference papers authored by our scientists and refine search by topic, location, year, and advanced search.

Filter Total Items: 5518

A novel origin for PGE reefs: A case study of the J-M Reef A novel origin for PGE reefs: A case study of the J-M Reef

The origin of meter scale stratiform layers of disseminated sulfides in enriched platinum group element (PGE) tenors and grades, called reef-type deposits, are the world’s most significant source of PGEs. Their origin in layered mafic intrusions remains debated, but in general, most researchers favor an orthomagmatic origin for reef-type deposits and agree that their formation requires...
Authors
Michael Jenkins, James E. Mungall, Michael L. Zientek, Gelu Costin, Zhuo-sen Yao

What did they just say? Building a Rosetta stone for geoscience and machine learning What did they just say? Building a Rosetta stone for geoscience and machine learning

Modern advancements in science and engineering are built upon multidisciplinary projects that bring experts together from different fields. Within their respective disciplines, researchers rely on precise terminology for specific ideas, principles, methods, and theories. Hence, the potential for miscommunication is substantial, especially when common words have been adopted by one (or...
Authors
Stanley Paul Mordensky, John Lipor, Erick R. Burns, Cary Ruth Lindsey

Scaling-up deep learning predictions of hydrography from IfSAR data in Alaska Scaling-up deep learning predictions of hydrography from IfSAR data in Alaska

The United States National Hydrography Dataset (NHD) is a database of vector features representing the surface water features for the country. The NHD was originally compiled from hydrographic content on U.S. Geological Survey topographic maps but is being updated with higher quality feature representations through flow-routing techniques that derive hydrography from high-resolution...
Authors
Larry Stanislawski, Ethan J. Shavers, Alexander Duffy, Philip T. Thiem, Nattapon Jaroenchai, Shaowen Wang, Zhe Jiang, Barry J. Kronenfeld, Barbara P. Buttenfield

Physics-guided graph meta learning for predicting water temperature and streamflow in stream networks Physics-guided graph meta learning for predicting water temperature and streamflow in stream networks

This paper proposes a graph-based meta learning approach to separately predict water quantity and quality variables for river segments in stream networks. Given the heterogeneous water dynamic patterns in large-scale basins, we introduce an additional meta-learning condition based on physical characteristics of stream segments, which allows learning different sets of initial parameters...
Authors
Shengyu Chen, Jacob Aaron Zwart, Xiaowei Jia
Was this page helpful?