Knowledge engineering. Data mining. Training.



Programming Bayesian Network Solutions with Netica
Owen Woodberry and Steven Mascaro
Provides an introduction to programming Bayesian Networks in Java with Netica. Assumes minimal programming experience and a basic understanding of BNs.
Bayesian Artificial Intelligence
Kevin B. Korb and Ann E. Nicholson
Updated and expanded, Bayesian Artificial Intelligence, Second Edition provides a practical and accessible introduction to the main concepts, foundation, and applications of Bayesian networks. It focuses on both the causal discovery of networks and Bayesian inference procedures. Adopting a causal interpretation of Bayesian networks, the authors discuss the use of Bayesian networks for causal modeling. They also draw on their own applied research to illustrate various applications of the technology.
Published by CRC Press


Ask us for a copy of any of these papers if you can't access the full text.

Mascaro, S., Wu, Y., Woodberry, O., Nyberg, E. P., Pearson, R., Ramsay, J. A., Mace, A. O., Foley, D. A., Snelling, T. L., Nicholson, A. E., et al. (2023). Modeling COVID-19 disease processes by remote elicitation of causal Bayesian networks from medical experts. BMC Medical Research Methodology, 23(1), 76.
Jamieson, L. E., Woodberry, O., Mascaro, S., Meurisse, N., Jaksons, R., Brown, S. D. J., & Ormsby, M. (2022). An integrated biosecurity risk assessment model (IBRAM) for evaluating the risk of import pathways for the establishment of invasive species. Risk Analysis, 42(6), 1325-1345.
Meurisse, N., Marcot, B. G., Woodberry, O., Barratt, B. I. P., & Todd, J. H. (2022). Risk Analysis Frameworks Used in Biological Control and Introduction of a Novel Bayesian Network Tool. Risk Analysis, 42(6), 1255-1276.
Mascaro, S., & Woodberry, O. (2022). A flexible method for parameterizing ranked nodes in Bayesian networks using Beta distributions. Risk Analysis, 42(6), 1179-1195.
Barons, M. J., Mascaro, S., & Hanea, A. M. (2022). Balancing the elicitation burden and the richness of expert input when quantifying discrete Bayesian networks. Risk Analysis, 42(6), 1196-1234.
McLeod, C., Norman, R., Wood, J., Mulrennan, S., Morey, S., Schultz, A., Messer, M., Spaapen, K., Stoneham, M., Wu, Y., Smyth, A., Blyth, C., Webb, S., Mascaro, S., Woodberry, O., & Snelling, T. (2021). Novel method to select meaningful outcomes for evaluation in clinical trials. BMJ Open Respiratory Research, 8(1), e000877.
Butt, N., Wenger, A. S., Lohr, C., Woodberry, O., Morris, K., & Pressey, R. L. (2021). Predicting and managing plant invasions on offshore islands. Conservation Science and Practice, 3(2), e192.
Wu, Y., Foley, D., Ramsay, J., Woodberry, O., Mascaro, S., Nicholson, A. E., & Snelling, T. (2021). Bridging the gaps in test interpretation of SARS-CoV-2 through Bayesian network modelling. Epidemiology and Infection, 149, e166.

Technical Reports


M. Samiullah, D. Albrecht, and A. Nicholson (2017). Supplementary materials: IOOBN framework and case study. Technical Report 2017/1, Bayesian Intelligence.


A. E. Nicholson, S. Mascaro, S. Thakur, K. B. Korb and R. Ashman (2016). Delphi Elicitation for Strategic Risk Assessment Technical Report 2016/1, Bayesian intelligence.


K.B. Korb and L. Brumley (2015). The Evolution of Utility, Or Why Is Sex Fun?. Technical Report 2015/1, Bayesian Intelligence.


S. Mascaro, K.B. Korb and A. Nicholson (2010). Learning Abnormal Vessel Behaviour from AIS Data with Bayesian Networks at Two Time Scales. Technical Report 2010/4, Bayesian Intelligence.
A. Nicholson, O. Woodberry and C. Twardy (2010). The "Native Fish" Bayesian networks. Technical Report 2010/3, Bayesian Intelligence. (BNs for this report.)
K.B. Korb and A. Dorin. (2010) Evolution and the Arrow of Complexity. TR 2010/2.
S.A. Zonneveldt, K.B. Korb and A.E. Nicholson (2010). Bayesian network classifiers for the German credit data. Technical Report 2010/1, Bayesian Intelligence.


K.B. Korb and A. Dorin (2009). A simulation of niche construction. Technical Report 2009/2, Bayesian Intelligence.
Y. Wen, K.B. Korb and A.E. Nicholson (2009). DataZapper: A Tool for Generating Incomplete Datasets. Technical Report 2009/1, Bayesian Intelligence.
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