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  5. A Deep Bayesian Active Learning Framework for Temporal Multimodal Data

A Deep Bayesian Active Learning Framework for Temporal Multimodal Data

Priyadip Ray | 19-ERD-009

Executive Summary

We will develop a high-performance, active-learning system for dynamic modeling that is capable of combining non-static data from disparate sources and learning the underlying temporal structure of that data in order to predict outcomes. This research has broad application in fields such as healthcare, energy, and nuclear non-proliferation.