Identifiability-based Experimental Design

Identifiability-Based Experimental Design is an experimental design framework that systematically selects input conditions, measurements, or interventions to maximize the structural and practical identifiability of model parameters within a given system.

22

Publications

1K

Citations

51

Authors

34

Institutions

Publications per year

2017–2026

6

Authors

51

  1. NS
    Ne‐Zheng Sun

    University of California, Los Angeles, United States

    3 publications · 70 citations

    3

    h-index

  2. MG
    M. Gevers

    UCLouvain, Belgium

    2 publications · 62 citations

    2

    h-index

  3. GX
    Gongjun Xu

    University of Michigan, United States

    2 publications · 145 citations

    2

    h-index

  4. AS
    Alexandre Sanfelice Bazanella

    Universidade Federal do Rio Grande do Sul, Brazil

    2 publications · 62 citations

    2

    h-index

  5. LM
    Ljubiša Mišković

    École Polytechnique Fédérale de Lausanne, Switzerland

    2 publications · 62 citations

    2

    h-index

1–5 of 51

Venues

  1. Water Resources Research

    2 publications · 60 citations

    2

    h-index

  2. Industrial & Engineering Chemistry Research

    2 publications · 75 citations

    2

    h-index

  3. Edinburgh Research Explorer (University of Edinburgh)

    Repository · 1 publications · 22 citations

    1

    h-index

  4. IET Systems Biology

    1 publications · 127 citations

    1

    h-index

  5. Journal of The Royal Society Interface

    1 publications · 29 citations

    1

    h-index

1–5