This article provides a retrospective on one such case: the TRIPS project at the University of Texas at Austin. This project started with early funding by the National Science Foundation (NSF) of ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?
As a data-driven analysis and decision-making tool, student portraits have gained significant attention in education ...
A new algorithmic framework that can predict flooding could help save lives and reduce the devastation as climate change drives more intense and unpredictable rainfall.
Researchers have developed an AI system that learns about the world via videos and demonstrates a notion of “surprise” when ...
New England's a complicated place, especially when it comes to flooding.
New NIH-funded research has led to an AI model that may better predict which children are at high risk for sepsis — before ...
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Making simulations more accurate than ever with deep learning
Future events such as the weather or satellite trajectories are computed in tiny time steps, so the computation must be both ...
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