Abstract: Quantum Machine Learning (QML) has emerged as a promising frontier within artificial intelligence, offering enhanced data-driven modeling through quantum-augmented representation, ...
High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.
Metals are made of randomly oriented crystals at the microscopic-length scale. The alignment of the crystal faces creates an infinite number of configurations and complex patterns, making simulations ...
By transforming movement into data, Timothy Dunn is reshaping how scientists can study behavior and the brain.
High-entropy alloys are promising advanced materials for demanding applications, but discovering useful compositions is difficult and expensive due to the vast number of possible element combinations.
Georgia Tech’s Qi Tang is building machine learning (ML) models to accelerate nuclear fusion research, making it more affordable and more accurate. Backed by a grant from the U.S. Department of Energy ...
Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered ...
In order to build the computers and devices of tomorrow, we have to understand how they use energy today. That's harder than it sounds. Memory storage, information processing, and energy use in these ...
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