Identifying optimal catalyst materials for specific reactions is crucial to advance energy storage technologies and sustainable chemical processes. To screen catalysts, scientists must understand ...
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...
When experiments are impractical, density functional theory (DFT) calculations can give researchers accurate approximations of chemical properties. The mathematical equations that underpin the ...
NTT Research and NTT R&D scientists presented 12 papers at ICML 2025, one of the world’s most prestigious conferences on AI and machine learning. Three papers co-authored by NTT Research Physics of AI ...
A rotating cylinder with its side cut away to expose the core, showing patches of purple, blue, green, yellow, and orange that are dense in the middle and more diffuse toward the edges. This rotating ...
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Machine learning algorithm enables faster, more accurate predictions on small tabular data sets
Filling gaps in data sets or identifying outliers—that's the domain of the machine learning algorithm TabPFN, developed by a team led by Prof. Dr. Frank Hutter from the University of Freiburg. This ...
POWDER Magazine on MSN
New AI Weather Model Is Designed for Predicting Snow in the Mountains
The model takes normal weather models and makes them higher resolution, before delivering them to OpenSnow subscribers.
News-Medical.Net on MSN
Early warning for diabetes: AI model identifies prediabetes risk with high accuracy
A Scientific Reports study developed a pattern neural network that integrates total antioxidant status with clinical and metabolic markers to predict prediabetes in Indian adults. The model achieved ...
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