Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news reporting out of Oak Ridge, Tennessee, by News Rx editors, research stated, “In recent years, deep learning has become an incre asingly popular alternative for modeling in geoscience applications due to its s calability and efficiency. However, the interpretability, compute, data volume, and hyperparameter tuning requirements of deep learning models make development and monitoring difficult.” Financial support for this research came from United States Department of Energy (DOE). Our news journalists obtained a quote from the research from Oak Ridge National Laboratory, “Furthermore, model explainability and communicating results obtaine d by these models to users or domain experts is a challenge, as domain experts i n geoscience also need to have a deep understanding of how those models function in order to support their scientific works. Here, we describe a science gateway and machine learning pipeline for predicting gravity anomalies from geophysical data. The gateway, built on open-source technologies, provides a holistic view of the pipeline through interactive visualizations aimed at enabling efficient e xploratory data analysis. The repeatability, reproducibility, and monitoring cap abilities of this overall system allow us to iterate and analyze at scale. Using this pipeline and gateway, we can repeatedly produce accurate high-resolution g ravity anomaly datasets.”
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