Research Review 2020, Knowing When You Don't Know: Engineering AI Systems in an Uncertain World
Abstract
In order for the DoD to leverage recent advances in AI, modern Machine Learning techniques need to be able to quantify, reason about, and rectify uncertainty in their predictions. In this work, we will benchmark modern techniques that quantify uncertainty, and develop techniques to identify causes of uncertainty and efficiently update ML models to reduce uncertainty in their predictions.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 2020
- Accession Number
- AD1111265
Entities
People
- Eric Heim
Organizations
- Carnegie Mellon University