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Nikita A. Sakhanenko, Ph.D. - Publications

Affiliations: 
2008 University of New Mexico, Albuquerque, NM, United States 
Area:
Computer Science, Artificial Intelligence
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7 high-probability publications. We are testing a new system for linking publications to authors. You can help! If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. If you identify any major omissions or other inaccuracies in the publication list, please let us know.

Year Citation  Score
2012 Sakhanenko NA, Galas DJ. Probabilistic logic methods and some applications to biology and medicine. Journal of Computational Biology : a Journal of Computational Molecular Cell Biology. 19: 316-36. PMID 22401592 DOI: 10.1089/cmb.2011.0234  0.313
2010 Sakhanenko NA, Luger GF. Model failure and context switching using logic-based stochastic models Journal of Computer Science and Technology. 25: 665-680. DOI: 10.1007/S11390-010-1052-0  0.695
2009 Sakhanenko NA, Luger GF, Makaruk HE, Holtkamp DB. Predictions and diagnostics in experimental data using support vector regression International Journal On Artificial Intelligence Tools. 18: 163-171. DOI: 10.1142/S0218213009000093  0.621
2008 Sakhanenko NA, Rammohan RR, Luger GF, Stern CR. A new approach to model-based diagnosis using probabilistic logic Proceedings of the 21th International Florida Artificial Intelligence Research Society Conference, Flairs-21. 678-683.  0.608
2007 Sakhanenko NA, Luger GF, Stern CR. Managing dynamic contexts using failure-driven stochastic models Proceedings of the Twentieth International Florida Artificial Intelligence Research Society Conference, Flairs 2007. 466-471.  0.704
2007 Sakhanenko NA, Rammohan RR, Luger GF, Stern CR. A context-partitioned stochastic modeling system with causally informed context management and model induction Proceedings of the 3rd Indian International Conference On Artificial Intelligence, Iicai 2007. 2172-2191.  0.63
2006 Sakhanenko NA, Luger GF, Makaruk HE, Aubrey JB, Holtkamp DB. Shock physics data reconstruction using support vector regression International Journal of Modern Physics C. 17: 1313-1325. DOI: 10.1142/S0129183106009813  0.601
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