George Mason University was awarded a $325,933 project grant from the National Science Foundation Division of Information and Intelligent Systems. The grant was awarded under the Computer and Information Science and Engineering program (CFDA 47.070) to support a three-year collaborative research project titled "Principled Uncertainty Quantification in Deep Learning Models for Time Series Analysis" from October 1, 2021 through September 30, 2024.
The project aims to advance the development of techniques for quantifying uncertainty in deep learning models applied to time series data analysis. The research is expected to help improve the reliability and trustworthiness of artificial intelligence systems used for applications involving sequential data such as health monitoring, forecasting, and anomaly detection. The funding will support investigator-initiated research activities at George Mason University to achieve the stated goals.
Generated 1/6/24, 5:43 PM