Factor Graph Optimization

Factor Graph Optimization is a probabilistic graphical model-based inference method that formulates estimation problems by factorizing joint probability distributions into variable nodes and factor nodes to enable efficient, structured optimization over nonlinear and non-Gaussian measurement models in inertial geodesy.

255

Publications

15.3K

Citations

751

Authors

244

Institutions

Publications per year

2017–2026

169

Authors

751

  1. LH
    Li‐Ta Hsu

    Hong Kong Polytechnic University, Hong Kong SAR China

    14 publications · 874 citations

    14

    h-index

  2. MK
    Michael Kaess

    Carnegie Mellon University, United States

    12 publications · 1.2K citations

    12

    h-index

  3. FD
    Frank Dellaert

    Georgia Institute of Technology, United States

    12 publications · 3.2K citations

    12

    h-index

  4. WW
    Weisong Wen

    Hong Kong Polytechnic University, Hong Kong SAR China

    10 publications · 604 citations

    10

    h-index

  5. LC
    Luca Carlone

    Massachusetts Institute of Technology, United States

    7 publications · 2.3K citations

    7

    h-index

1–5 of 751

Venues

  1. IEEE Robotics and Automation Letters

    19 publications · 1.3K citations

    19

    h-index

  2. IEEE Sensors Journal

    9 publications · 295 citations

    9

    h-index

  3. IEEE Access

    9 publications · 194 citations

    9

    h-index

  4. arXiv (Cornell University)

    Repository · 8 publications · 241 citations

    8

    h-index

  5. 8

    h-index

1–5