Research from PNNL and the University of Washington demonstrates the extension of the MBE for periodic systems and its use to decompose the lattice energies of different ice polymorphs.
To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.
COVID-19 infections at PNNL early in the pandemic were caused by a wide variety of viral sequences, according to a new analysis by Laboratory researchers.
Three PNNL authored papers were accepted as posters to the ICLR 2023 Workshop on Physics for Machine Learning and Workshop on Mathematical and Empirical Understanding of Foundation Models.
Bobbie-Jo Webb-Robertson is a leader with a PhD in decision sciences & engineering systems from Rensselaer Polytechnic Institute and experience in managing complex scientific programs and line organizations. She assumed the role 3/13/23.
Machine learning models help identify important environmental properties that influence how often extreme rain events occur with critical intensity and duration.
Gosline works to develop computational algorithms that are uniquely targeted for rare disease work by doing foundational research in model system development. This work can be expanded to all model systems in human disease.
