Uncertainty Estimation

Uncertainty Estimation is a methodological task in robot perception that consists in quantifying the epistemic and aleatoric uncertainty of sensory data processing and model predictions, typically by producing probabilistic measures or confidence scores that can inform subsequent perception, planning, and control.

8.9K

Publications

521.4K

Citations

19.6K

Authors

3.8K

Institutions

Publications per year

2017–2026

2.9K

Authors

19.6K

  1. CS
    Christian Soize

    Laboratoire Modélisation et Simulation Multi-Echelle, France

    27 publications · 1.8K citations

    22

    h-index

  2. SM
    Sankaran Mahadevan

    Vanderbilt University, United States

    29 publications · 1.8K citations

    22

    h-index

  3. YG
    Yarin Gal

    University of Oxford, United Kingdom

    26 publications · 8.9K citations

    21

    h-index

  4. XH
    Xu Han

    Hunan University, China

    27 publications · 1.5K citations

    20

    h-index

  5. JH
    J.C. Helton

    Arizona State University, United States

    17 publications · 7.2K citations

    17

    h-index

1–5 of 19.6K

Venues

  1. Reliability Engineering & System Safety

    127 publications · 15.5K citations

    59

    h-index

  2. arXiv (Cornell University)

    Repository · 232 publications · 23.4K citations

    53

    h-index

  3. IEEE Transactions on Automatic Control

    113 publications · 13.3K citations

    45

    h-index

  4. Mechanical Systems and Signal Processing

    MSSP · 103 publications · 5.5K citations

    41

    h-index

  5. 38

    h-index

1–5