Researchers at the Department of Energy's SLAC National Accelerator Laboratory and collaborating institutions recently built a generative AI model that can recreate molecular structures from the movement of the molecule's ...
New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings of the IEEE International ...
Reliable and scalable water level prediction is crucial in hydrology for effective water resources management, especially when considering challenges owing to climate change, urbanization, improper land use, and high-water ...
The DNA foundation model Evo 2 has been published in the journal Nature. Trained on the DNA of over 100,000 species across the entire tree of life, Evo 2 can identify patterns in gene sequences across disparate organisms ...
A new computational method allows modern atomic models to learn from experimental thermodynamic data, according to a University of Michigan Engineering and Université Paris-Saclay study published in Nature Communications. ...
By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major breakthrough toward solving ...
The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle collisions at the LHC. This new approach can reconstruct collisions more quickly and precisely than traditional ...
For years, Iceland, Switzerland, and Norway have ranked near the top of the United Nations' annual index of countries based on indicators of well-being and quality of life. Countries with more poverty and less access to health ...
Keeping high-power particle accelerators at peak performance requires advanced and precise control systems. For example, the primary research machine at the U.S. Department of Energy's Thomas Jefferson National Accelerator ...
A multi-institutional team of researchers led by Virginia Tech's Fralin Biomedical Research Institute at VTC has for the first time identified specific patterns of brain chemical activity that predict how quickly individual ...
