Timeseries-aware Uncertainty Wrappers for Uncertainty Quantification of Information-Fusion-Enhanced AI Models based on Machine Learning

by   Janek Groß, et al.

As the use of Artificial Intelligence (AI) components in cyber-physical systems is becoming more common, the need for reliable system architectures arises. While data-driven models excel at perception tasks, model outcomes are usually not dependable enough for safety-critical applications. In this work,we present a timeseries-aware uncertainty wrapper for dependable uncertainty estimates on timeseries data. The uncertainty wrapper is applied in combination with information fusion over successive model predictions in time. The application of the uncertainty wrapper is demonstrated with a traffic sign recognition use case. We show that it is possible to increase model accuracy through information fusion and additionally increase the quality of uncertainty estimates through timeseries-aware input quality features.


page 1

page 2

page 3

page 4


A view on model misspecification in uncertainty quantification

Estimating uncertainty of machine learning models is essential to assess...

AI Model Utilization Measurements For Finding Class Encoding Patterns

This work addresses the problems of (a) designing utilization measuremen...

Robustifying Controller Specifications of Cyber-Physical Systems Against Perceptual Uncertainty

Formal reasoning on the safety of controller systems interacting with pl...

Building Safe and Reliable AI systems for Safety Critical Tasks with Vision-Language Processing

Although AI systems have been applied in various fields and achieved imp...

Architectural patterns for handling runtime uncertainty of data-driven models in safety-critical perception

Data-driven models (DDM) based on machine learning and other AI techniqu...

Uncertainty Aware AI ML: Why and How

This paper argues the need for research to realize uncertainty-aware art...

Constraining Model Uncertainty in Plasma Equation-of-State Models with a Physics-Constrained Gaussian Process

Equation-of-state (EOS) models underpin numerical simulations at the cor...

Please sign up or login with your details

Forgot password? Click here to reset