Research Explorer

Project

A probabilistic programming approach to the analysis of high-dimensional biological monitoring data.
Code
01N16019
Duration
01 September 2020 → 30 June 2025
Funding
Regional and community funding: Special Research Fund
Research disciplines
  • Natural sciences
    • Computer science
    • Machine learning and decision making
Keywords
Multivariate data analysis numerical optimization phenotyping
 
Project description
 

Plant phenotyping studies or studies that monitor of animal or human behavior often rely on the collection and analysis of high-dimensional and (spatio-) temporal datasets. In this research project, probabilistic programming approaches will be developed that allow to incorporate prior knowledge on the study objects (e.g., shape or behavior) into the data analysis pipeline to make the analysis more robust.