Despite the excitement surrounding generative AI, the data shows that scientific research is still powered primarily by ...

Kernel methods represent a cornerstone in modern machine learning, enabling algorithms to efficiently derive non-linear patterns by implicitly mapping data into high‐dimensional feature spaces. At the ...

Artificial intelligence is increasingly used to integrate and analyze multiple types of data formats, such as text, images, ...

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...

MIT researchers have developed a method that generates more accurate uncertainty measures for certain types of estimation.

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 ...

India ranks third globally in machine learning-driven scientific research, as per the ML Global Impact Report 2025. With its expanding network of universities, national laboratories, and startups, ...

A scientist in Sweden has developed a new hybrid local features-based method using thermographs to identify faulty solar panels. A researcher from Sweden’s Jönköping University has proposed a machine ...

Software engineers are increasingly seeking structured pathways to transition into machine learning roles as companies expand ...

Jordan Awan receives funding from the National Science Foundation and the National Institute of Health. He also serves as a privacy consultant for the federal non-profit, MITRE. In statistics and ...

The U.S. Supreme Court today declined to grant a petition filed by Recentive Analytics, Inc. asking the Court to weigh in on ...