TIMELIGHT: EXPLAINABILITY IN TIME SERIES
Abstract
The PI introduces TIMELIGHT, an end-to-end System for explainability in time series; investigating how to build an effective and scalable system for explainability of time-series models. The main focus is on explainability in blackbox models of time series. There are four critical aspects one must address to develop a successful solution. They include: (1) Explaining Predictions in Time Series, (2) Explaining High-Dimensional Predictions in Time Series, (3) Interpretably Closing the Loop through Explanations and (4) End-to-End System for Explainability in Time Series.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 12, 2021
- Source ID
- FA95502010427
Entities
People
- Emily B. Fox
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Washington