When two powerful earthquakes rocked southern California earlier this month, officials’ attention focused, understandably, on safety. How many people were injured? Were buildings up to code? How good are we at predicting earthquakes?
Researchers at PNNL are applying deep learning techniques to learn more about neutrinos, part of a worldwide network of researchers trying to understand one of the universe’s most elusive particles.
Researchers have come up with a new method for creating synthetic “colored” nanodiamonds, a step on the path to realization of quantum computing, which promises to solve problems far beyond the abilities of current supercomputers.
Patricia Huestis, a collaborator in the Interfacial Dynamics in Radioactive Environments and Materials (IDREAM) Energy Frontier Research Center, has been awarded the DOE Office of Science Graduate Student Research (SCGSR) award.
Scientists created a fast-track tutorial that equips a neural network to tackle drug discovery and other applications where there's a shortage of precisely labeled chemical data.
PNNL scientists today unveiled an updated tool designed to help stakeholders assess the nation's preparedness for biological-based dangers, also known as biothreats.
Scientists are exploring the use of deep neural network to interpret highly technical data related to national security, the environment and the cosmos.
