Berkeley Lab: With Little Training, Machine-Learning Algorithms Can Uncover Hidden Scientific Knowledge

Berkeley Lab: With Little Training, Machine-Learning Algorithms Can Uncover Hidden Scientific Knowledge. “Sure, computers can be used to play grandmaster-level chess, but can they make scientific discoveries? Researchers at the U.S. Department of Energy’s Lawrence Berkeley National Laboratory have shown that an algorithm with no training in materials science can scan the text of millions of papers and uncover new scientific knowledge.”

Berkeley Lab: Berkeley Lab Team Uses Deep Learning to Help Veterans Administration Address Suicide Risks

Berkeley Lab: Berkeley Lab Team Uses Deep Learning to Help Veterans Administration Address Suicide Risks. “Researchers in the Computational Research Division (CRD) at Lawrence Berkeley National Laboratory (Berkeley Lab) are applying deep learning and analytics to electronic health record (EHR) data to help the Veterans Administration (VA) address a host of medical and psychological challenges affecting many of the nation’s 700,000 military veterans.”

Berkeley Lab: Berkeley Lab ‘Minimalist Machine Learning’ Algorithms Analyze Images From Very Little Data

Berkeley Lab: Berkeley Lab ‘Minimalist Machine Learning’ Algorithms Analyze Images From Very Little Data . “Mathematicians at the Department of Energy’s Lawrence Berkeley National Laboratory (Berkeley Lab) have developed a new approach to machine learning aimed at experimental imaging data. Rather than relying on the tens or hundreds of thousands of images used by typical machine learning methods, this new approach ‘learns’ much more quickly and requires far fewer images.”

Berkeley Lab: Berkeley Lab’s ArrayUDF Tool Turns Large-scale Scientific Array Data Analysis Into a Cakewalk

Berkeley Lab: Berkeley Lab’s ArrayUDF Tool Turns Large-scale Scientific Array Data Analysis Into a Cakewalk. “A novel scalable framework developed by researchers in the Lawrence Berkeley National Laboratory’s (Berkeley Lab’s) Computational Research Division (CRD) and at UC Merced is improving scientific productivity by allowing researchers to run user-defined custom analysis operations on large arrays of data with massively parallel supercomputers, while leaving complex data management and performance optimization tasks up to the underlying system.”

Lawrence Berkeley Laboratory: New Data Archive Aims to Amplify Impact of Ecosystem Research

Lawrence Berkeley National Laboratory: New Data Archive Aims to Amplify Impact of Ecosystem Research. “As environmental scientists move towards understanding earth systems at greater resolution than ever before, it’s critical that they have access to needed data sets. Yet much of these data are not archived, publicly available, or collected in a standardized format, due to the multiple challenges of coordinating efforts across independent research groups and institutions worldwide. Now researchers at Berkeley Lab are taking action to address these challenges. Thanks to $3.6 million in funding from the U.S. Department of Energy (DOE)’s Office of Science, the Lab’s Computing Sciences and Earth & Environmental Sciences Area (EESA) are partnering on a three-year project to develop an archive that will serve as a repository for hundreds of DOE-funded research projects under the agency’s Environmental System Science (ESS) umbrella.”