Machine learning and other modeling approaches could aid in forecasting the arrival of floating Sargassum rafts that clog ...

In 1854, London was struck by a devastating cholera outbreak. Public authorities responded using the best tools and scientific understanding available at the time.Disease was widely believed to spread ...

From fine-tuning open source models to building agentic frameworks on top of them, the open source world is ripe with ...

People with spinal cord injuries often lose movement even though their brains still send the right signals. Researchers ...

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data other than what they were trained on, raising questions about the need to ...

Abstract: Accurate rainfall nowcasting remains one the most challenging tasks in weather forecasting. Previous studies mainly developed rainfall forecast models by combining GNSS derived precipitable ...

Machine vision is a collection of technologies that give automated equipment a high-level understanding of the immediate environment from images. Without machine vision software, digital images would ...

Artificial intelligence (AI) has been making great strides in generating and translating human language. Large language models (LLMs) have quickly moved beyond simply dealing with human speech to ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses the kernel matrix inverse (Cholesky ...

Abstract: In lifelong learning, data are used to improve performance not only on the present task, but also on past and future (unencountered) tasks. While typical transfer learning algorithms can ...

A team of academics has used a simple machine learning algorithm to filter out so-called noisy trading in stock exchange data and say they have generated more-powerful versions of signals already ...