Using artificial intelligence to find anomalies hiding in massive

Researchers at the MIT-IBM Watson AI lab have developed a computationally efficient method that could be used to identify anomalies in the U.S. power grid in real time. The novel technique augments a special type of machine-learning model with a powerful graph structure, and does not require any labeled data to train.

Department of Energy (DoE), MIT News

Artificial intelligence, MIT News

New Open-Source System Developed to Manage and Share Complex Datasets

Kimerle anomaly, Radiology Case

Using artificial intelligence to find anomalies hiding in massive

Graph Deep Learning Archives - MIT-IBM Watson AI Lab

Matteo V. on LinkedIn: Using artificial intelligence to find

Using Artificial Intelligence to Find Anomalies Hiding in Massive

Müllerian duct anomaly classification