Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model (LLM) agents to dynamically adapt to their environment without fine-tuning ...

Researchers claim model can cut years from testing cycles Scientists have developed a machine learning method that could ...

Real-world data typically exhibits long-tailed class distribution and contains label noise. Previous long-tail learning ...

Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...

Researchers have demonstrated, for the first time, that transfer learning can significantly enhance material Z-class identification in muon tomography, even in scenarios with limited or completely ...

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.

South Korean researchers have developed a guided-learning framework that accurately predicts PV power without requiring irradiance sensors during operation, using routine meteorological data instead.