Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...
The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in research applications to explore potentially high-impact approaches in the development and use of ...
In 2018, climate simulations were the third-largest use of computing cycles at a leading U.S. supercomputing cluster. The study of quarks and other subatomic particles came in second. Topping the list ...
Deep learning models have shown great potential in predicting and engineering functional enzymes and proteins. Does this prowess extend to other fields of biology as well? Contrary to expectations, a ...
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Overparameterized neural networks: Feature learning precedes overfitting, research finds
Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...
Scientists and institutions dedicate more resources each year to the discovery of novel materials to fuel the world. As natural resources diminish and the demand for higher value and advanced ...
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This year’s winner of Best use of machine learning/AI, ActiveViam stood out for delivering a practical, production-ready ...
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