The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.
Learning dynamic Bayesian networks
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Citations
Cites
Maximum Likelihood from Incomplete Data Via the EM Algorithm
Dempster, A. P., Laird, N. M., & Rubin, D. B. (1977) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1977.tb01600.x · Cited by 50,444
Stochastic relaxation, gibbs distributions, and the bayesian restoration of images.
Geman, S., & Geman, D. (1984) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.1984.4767596 · Cited by 17,949
(1988) · Cited by 16,582
Classification And Regression Trees
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (2017) · doi:10.1201/9781315139470 · Cited by 11,417
Rockafellar, R. T. (1970) · Princeton University Press eBooks · doi:10.1515/9781400873173 · Cited by 10,801
Error bounds for convolutional codes and an asymptotically optimum decoding algorithm
Viterbi, A. (1967) · IEEE Transactions on Information Theory · doi:10.1109/tit.1967.1054010 · Cited by 6,759
Spatial Interaction and the Statistical Analysis of Lattice Systems
Besag, J. (1974) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1974.tb00999.x · Cited by 6,067
Adaptive Mixtures of Local Experts
Jacobs, R. A., Jordan, M. I., Nowlan, S. J., & Hinton, G. E. (1991) · Neural Computation · doi:10.1162/neco.1991.3.1.79 · Cited by 5,384
An introduction to hidden Markov models
Rabiner, L., & Juang, B. (1986) · IEEE ASSP Magazine · doi:10.1109/massp.1986.1165342 · Cited by 4,775
Adaptive filtering, prediction and control
Ioannou, P. (1985) · Automatica · doi:10.1016/0005-1098(85)90014-7 · Cited by 4,480
Cited by
Inferring Networks of Diffusion and Influence
Gomez-Rodriguez, M., Leskovec, J., & Krause, A. (2012) · ACM Transactions on Knowledge Discovery from Data · doi:10.1145/2086737.2086741 · Cited by 445
Braun, D. A., Mehring, C., & Wolpert, D. M. (2010) · Behavioural Brain Research · doi:10.1016/j.bbr.2009.08.031 · Cited by 210
Calabrese, M., Cimmino, M., Fiume, F., Manfrin, M., Romeo, L., Ceccacci, S., Paolanti, M., Toscano, G., Ciandrini, G., Carrotta, A., et al. (2020) · Information · doi:10.3390/info11040202 · Cited by 158
Sousa, H. S., Machado, J. S., Branco, J. M., & Lourenço, P. B. (2015) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2015.05.127 · Cited by 16
Introspective perception for mobile robots
Rabiee, S., & Biswas, J. (2023) · Artificial Intelligence · doi:10.1016/j.artint.2023.103999 · Cited by 6
Metadata
- Authors
- Ghahramani, Z.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 1998
- Pages
- 168-197
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1541680420
- Cited by
- 543
- References
- 39
- FWCI
- 4.77
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Learning dynamic Bayesian networks. https://app.cochat.ai/papers/10.1007/bfb0053999
- The paper
- Ghahramani, Z. (1998). Learning dynamic Bayesian networks. Lecture Notes in Computer Science. https://doi.org/10.1007/bfb0053999
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
