AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks

Favorite Posted by Urs Köster, Software Engineer, Google Research Time series problems are ubiquitous, from forecasting weather and traffic patterns to understanding economic trends. Bayesian approaches start with an assumption about the data’s patterns (prior probability), collecting evidence (e.g., new time series data), and continuously updating that assumption to form

Read More
Shared by Google AI Technology March 28, 2024

Computer-aided diagnosis for lung cancer screening

Favorite Posted by Atilla Kiraly, Software Engineer, and Rory Pilgrim, Product Manager, Google Research Lung cancer is the leading cause of cancer-related deaths globally with 1.8 million deaths reported in 2020. Late diagnosis dramatically reduces the chances of survival. Lung cancer screening via computed tomography (CT), which provides a detailed

Read More
Shared by Google AI Technology March 20, 2024