Latent State Estimation

Latent State Estimation is the statistical inference process归属于 state-space modeling that specifically involves determining the unobserved system states from noisy measurements, distinguished by its reliance on probabilistic filtering or smoothing techniques to recover hidden dynamics over time.

190

Publications

8.3K

Citations

576

Authors

294

Institutions

Publications per year

2017–2026

95

Authors

576

  1. UP
    Ulrich Paquet

    Microsoft Research (United Kingdom), United Kingdom

    4 publications · 580 citations

    4

    h-index

  2. OW
    Ole Winther

    Technical University of Denmark, Denmark

    4 publications · 580 citations

    4

    h-index

  3. MF
    M. Fraccaro

    University of Pavia, Italy

    4 publications · 580 citations

    4

    h-index

  4. SR
    Stephen Roberts

    University of Oxford, United Kingdom

    4 publications · 185 citations

    4

    h-index

  5. ME
    Michael Eid

    Freie Universität Berlin, Germany

    3 publications · 538 citations

    3

    h-index

1–5 of 576

Venues

  1. arXiv (Cornell University)

    Repository · 17 publications · 771 citations

    14

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 6 publications · 261 citations

    6

    h-index

  3. IEEE Transactions on Signal Processing

    5 publications · 134 citations

    5

    h-index

  4. PLoS Computational Biology

    4 publications · 112 citations

    4

    h-index

  5. Journal of Econometrics

    4 publications · 151 citations

    4

    h-index

1–5