Probabilistic Mapping

Probabilistic Mapping is a formal method within the domain of spatial or conceptual representation that assigns likelihood distributions to possible correspondences between source and target elements, distinguishing itself from deterministic approaches by explicitly quantifying uncertainty in the mapping process.

181

Publications

16K

Citations

662

Authors

289

Institutions

Publications per year

2017–2026

58

Authors

662

  1. ST
    Sebastian Thrun

    Carnegie Mellon University, United States

    8 publications · 1K citations

    8

    h-index

  2. MA
    Martin Adams

    Nanyang Technological University, Singapore

    5 publications · 379 citations

    5

    h-index

  3. FP
    Frank Pfenning

    Carnegie Mellon University, United States

    4 publications · 169 citations

    4

    h-index

  4. WB
    Wolfram Burgard

    University of Freiburg, Germany

    4 publications · 362 citations

    4

    h-index

  5. KZ
    Karl Zilles

    Heinrich Heine University Düsseldorf, Germany

    4 publications · 977 citations

    4

    h-index

1–5 of 662

Venues

  1. arXiv (Cornell University)

    Repository · 6 publications · 211 citations

    6

    h-index

  2. IEEE Transactions on Robotics

    4 publications · 407 citations

    4

    h-index

  3. The International Journal of Robotics Research

    IJRR · 4 publications · 598 citations

    4

    h-index

  4. Cerebral Cortex

    4 publications · 918 citations

    4

    h-index

  5. IEEE Robotics and Automation Letters

    4 publications · 452 citations

    4

    h-index

1–5