This work shows that linear pattern scaling is an effective means of obtaining global-to-local relationships for CMIP6 models, as it has been in past model eras.
PNNL biodefense experts seek to identify, understand and mitigate the risks of biological pathogens—whether naturally occurring or intentionally created—so steps can be taken to prepare and respond.
In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
At the 2024 Aviation Futures Workshop, researchers from PNNL joined other subject matter experts and representatives from the stakeholder community in reimagining the passenger experience.
Cloud and its radiative effect are among the determining processes for the energy balance of the global climate; they are also the most challenging processes for the climate models to simulate.
Neeraj Kumar discusses how AI can transform scientific research at the Platform for Advanced Scientific Computing Conference and Trillion Parameter Consortium European Workshop.
At the Joint Statistical Meeting, the largest gathering of statisticians and data scientists in North America, PNNL researchers presented their latest findings and led a workshop on text analysis and natural language processing.
Lauren Charles, a chief data scientist at PNNL, will be presenting at the Forum on Microbial Threats for the National Academies of Sciences, Engineering, and Medicine.
