Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
Identifying optimal catalyst materials for specific reactions is crucial to advance energy storage technologies and sustainable chemical processes. To screen catalysts, scientists must understand ...
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 ...
Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
Scientists have developed and tested a deep-learning model that could support clinicians by providing accurate results and clear, explainable insights – including a model-estimated probability score ...
That challenge is examined in the study Towards Eco-Friendly Cybersecurity: Machine Learning-Based Anomaly Detection with ...
The study, titled Conditional Adversarial Fragility in Financial Machine Learning under Macroeconomic Stress, published as a ...
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