Robust Bayesian Filtering

Robust Bayesian Filtering is a Bayesian filtering framework distinguished by its ability to maintain accurate state estimation under model misspecification, outliers, or heavy-tailed noise through adaptive or bounded-influence mechanisms.

73

Publications

4.6K

Citations

190

Authors

94

Institutions

Publications per year

2017–2026

32

Authors

190

  1. JB
    Joseph B. Kadane

    Carnegie Mellon University, United States

    4 publications · 800 citations

    4

    h-index

  2. ER
    Edward R. Dougherty

    Texas A&M University, United States

    4 publications · 146 citations

    4

    h-index

  3. YZ
    Yonggang Zhang

    Harbin Engineering University, China

    3 publications · 772 citations

    3

    h-index

  4. NL
    Ning Li

    Harbin Engineering University, China

    2 publications · 709 citations

    3

    h-index

  5. EM
    Elı́as Moreno

    Universidad de Granada, Spain

    3 publications · 683 citations

    3

    h-index

1–5 of 190

Venues

  1. 4

    h-index

  2. Journal of Statistical Planning and Inference

    4 publications · 74 citations

    4

    h-index

  3. IEEE Transactions on Signal Processing

    3 publications · 113 citations

    3

    h-index

  4. 3

    h-index

  5. Signal Processing

    2 publications · 80 citations

    2

    h-index

1–5