At a conference featuring the most advanced computing hardware and software, ML in its various guises was on full display and highlighted by Nathan Baker’s featured invited presentation.
Through her role in the Department of Energy’s Advanced Scientific Computing Research-supported ExaLearn project, Jenna Pope is developing deep learning approaches for finding optimal water cluster structures for a variety of applications.
Scientists at PNNL are bringing artificial intelligence into the quest to see whether computers can help humans sift through a sea of experimental data.
B3? E4? Remember the board game Battleship? One player suggests a set of coordinates to another, hoping to find the elusive location of an unseen vessel.That is a good place to start in assessing the search for dark matter.
In today’s digital age, the rabbit hole of connected information can be not only a time sink, but downright overwhelming. Even for high-performance computers.
Twenty-four analysts from U.S. intelligence organizations met in August for a machine learning activity with PNNL researchers Nicole Nichols, Jeremiah Rounds, Lawrence Phillips, and Brian Kritzstein.
A gathering of international experts in Portland, Oregon, explored the future of electron microscopy and surfaced potential solutions in areas including new instrument designs, high-speed detectors, and data analytics capabilities.
Trouble on the electric grid might start with something relatively small: a downed power line, or a lightning strike at a substation. What happens next?
Pacific Northwest National Laboratory is leading efforts to address next-generation computing’s critical role in protecting the nation from cybersecurity threats.
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.
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.
Researchers used novel methods to safely create and analyze plutonium samples. The approaches could prove influential in future studies of the radioactive material, benefitting research in legacy, national security and nuclear fuels.