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The ALARM Monitoring System: A Case Study with two Probabilistic Inference Techniques for Belief Networks
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Citations
Cited by
Learning Bayesian networks from data: An information-theory based approach
Cheng, J., Greiner, R., Kelly, J., Bell, D., & Liu, W. (2002) · Artificial Intelligence · doi:10.1016/s0004-3702(02)00191-1 · Cited by 803
A Bayesian Approach to Learning Bayesian Networks with Local Structure
Chickering, D. M., Heckerman, D. E., & Meek, C. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1302.1528 · Cited by 314
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
Heckerman, D., Geiger, D., & Chickering, D. M. (1994) · Uncertainty Proceedings 1994 · doi:10.1016/b978-1-55860-332-5.50042-0 · Cited by 261
D’ya Like DAGs? A Survey on Structure Learning and Causal Discovery
Vowels, M. J., Camgoz, N. C., & Bowden, R. (2023) · ACM Computing Surveys · doi:10.1145/3527154 · Cited by 237
Discovering study-specific gene regulatory networks
Bo, V., Curtis, T., Lysenko, A., Saqi, M., Swift, S., & Tucker, A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106524 · Cited by 10
Metadata
- Authors
- Beinlich, I. A., Suermondt, H. J., Chavez, R. M., & Cooper, G. F.
- Venue
- Lecture Notes in Medical Informatics
- Publisher
- Springer Berlin Heidelberg
- Published
- 1989
- Pages
- 247-256
- ISSN
- 0172-7788 (ISSN-L)
- OpenAlex
- W1505477995
- Cited by
- 724
- References
- 0
- FWCI
- 9.63
- Type
- book chapter
- Language
- en
- Open access
- closed
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How to cite
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- CoChat. (2026). Citation check: The ALARM Monitoring System: A Case Study with two Probabilistic Inference Techniques for Belief Networks. https://app.cochat.ai/papers/10.1007/978-3-642-93437-7_28
- The paper
- Beinlich, I. A., Suermondt, H. J., Chavez, R. M., & Cooper, G. F. (1989). The ALARM Monitoring System: A Case Study with two Probabilistic Inference Techniques for Belief Networks. Lecture Notes in Medical Informatics. https://doi.org/10.1007/978-3-642-93437-7_28
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.
