Researchers developed NiCLIP, an AI model that decodes cognitive tasks, concepts, and domains from brain activation patterns. Trained on over 23,000 papers, NiCLIP excels at group-level decoding, ...
A study of 148 built-up cold-formed steel column tests found that machine-learning corrections performed well within the database but transferred poorly to unseen experimental programmes, limiting ...
A machine learning study of 532 older cancer patients with PICCs found that simple logistic regression outperformed complex ...
Self-supervised learning creates training targets from the structure of unlabeled data, allowing models to learn ...
The tool boosts the ability of physics- and AI-based forecasting models to predict typical and extreme weather events.
Stony Brook University researchers are developing tools to predict how much energy machine-learning models consume and help ...
Distributed AI training coordinates data, parameters, activations, gradients, and optimizer state across many accelerators so ...
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