Year |
Citation |
Score |
2019 |
Dickson DW, Baker MC, Jackson JL, DeJesus-Hernandez M, Finch NA, Tian S, Heckman MG, Pottier C, Gendron TF, Murray ME, Ren Y, Reddy JS, Graff-Radford NR, Boeve BF, Petersen RC, ... ... Sheppard JW, et al. Extensive transcriptomic study emphasizes importance of vesicular transport in C9orf72 expansion carriers. Acta Neuropathologica Communications. 7: 150. PMID 31594549 DOI: 10.1186/S40478-019-0797-0 |
0.52 |
|
2019 |
Scherrer B, Sheppard J, Jha P, Shaw J. Hyperspectral Imaging and Neural Networks to Classify Herbicide-Resistant Weeds Journal of Applied Remote Sensing. 13. DOI: 10.1117/1.Jrs.13.044516 |
0.381 |
|
2019 |
Perreault L, Sheppard J. Compact Structures for Continuous Time Bayesian Networks International Journal of Approximate Reasoning. 109: 19-41. DOI: 10.1016/J.Ijar.2019.03.005 |
0.655 |
|
2018 |
Dehghanpour K, Nehrir HM, Sheppard JW, Kelly NC. Agent-Based Modeling of Retail Electrical Energy Markets with Demand Response Ieee Transactions On Smart Grid. 9. DOI: https://doi.org/10.1109/TSG.2016.2631453 |
0.227 |
|
2018 |
Dehghanpour K, Nehrir MH, Sheppard JW, Kelly NC. Agent-Based Modeling of Retail Electrical Energy Markets With Demand Response Ieee Transactions On Smart Grid. 9: 3465-3475. DOI: 10.1109/Tsg.2016.2631453 |
0.401 |
|
2018 |
Sheppard JW, Strasser S. Multiple fault diagnosis using factored evolutionary algorithms Ieee Instrumentation & Measurement Magazine. 21: 27-38. DOI: 10.1109/Mim.2018.8423743 |
0.768 |
|
2017 |
Strasser S, Sheppard J, Fortier N, Goodman R. Factored Evolutionary Algorithms,” IEEE Transactions on Evolutionary Computation Ieee Transactions On Evolutionary Computation. 21: 281-293. DOI: https://doi.org/10.1109/TEVC.2016.2601922 |
0.331 |
|
2017 |
Strasser S, Sheppard J, Fortier N, Goodman R. Factored Evolutionary Algorithms Ieee Transactions On Evolutionary Computation. 21: 281-293. DOI: 10.1109/Tevc.2016.2601922 |
0.685 |
|
2017 |
Sturlaugson L, Perreault L, Sheppard J. Factored Performance Functions and Decision Making in Continuous Time Bayesian Networks Journal of Applied Logic. 22: 28-45. DOI: 10.1016/J.Jal.2016.11.030 |
0.465 |
|
2017 |
Perreault L, Thornton M, Sheppard J, DeBruycker J. Disjunctive Interaction in Continuous Time Bayesian Networks International Journal of Approximate Reasoning. 90: 253-271. DOI: 10.1016/J.Ijar.2017.07.011 |
0.654 |
|
2016 |
Dehghanpour K, Nehrir MH, Sheppard JW, Kelly N. Agent-Based Decision Making in Electrical Energy Markets Using Dynamic Bayesian Networks and Sparse Bayesian Learning Ieee Transactions On Power Systems. 31: 4744-4754. DOI: https://doi.org/10.1109/TPWRS.2016.2524678 |
0.263 |
|
2016 |
Sturlaugson L, Sheppard JW. Uncertain Evidence in Continuous Time Bayesian Networks International Journal of Approximate Reasoning. 70: 99-122. DOI: https://doi.org/10.1016/j.ijar.2015.12.013 |
0.326 |
|
2016 |
Strasser S, Goodman R, Sheppard J, Butcher S. A new discrete Particle Swarm Optimization algorithm Gecco 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference. 53-60. DOI: 10.1145/2908812.2908935 |
0.365 |
|
2016 |
Dehghanpour K, Nehrir MH, Sheppard JW, Kelly NC. Agent-Based Modeling in Electrical Energy Markets Using Dynamic Bayesian Networks Ieee Transactions On Power Systems. DOI: 10.1109/Tpwrs.2016.2524678 |
0.415 |
|
2016 |
Perreault LJ, Thornton M, Goodman R, Sheppard JW. A swarm-based approach to learning phase-type distributions for continuous time Bayesian networks Proceedings - 2015 Ieee Symposium Series On Computational Intelligence, Ssci 2015. 1860-1867. DOI: 10.1109/SSCI.2015.259 |
0.326 |
|
2016 |
Donnelly PJ, Sheppard JW. Cross-Dataset Validation of Feature Sets in Musical Instrument Classification Proceedings - 15th Ieee International Conference On Data Mining Workshop, Icdmw 2015. 94-101. DOI: 10.1109/ICDMW.2015.213 |
0.595 |
|
2016 |
Sturlaugson L, Sheppard JW. Uncertain and negative evidence in continuous time Bayesian networks International Journal of Approximate Reasoning. 70: 99-122. DOI: 10.1016/J.Ijar.2015.12.013 |
0.733 |
|
2015 |
Wang C, Miller CJ, Nehrir MH, Sheppard JW, McElmurry SP. A Load Profile Management Integrated Power Dispatch Using a Newton-Like Particle Swarm Optimization Method Sustainable Computing: Informatics and Systems. 8: 8-17. DOI: https://doi.org/10.1016/j.suscom.2014.10.001 |
0.236 |
|
2015 |
Fortier N, Sheppard JW, Strasser S. Abductive Inference in Bayesian Networks using Distributed Overlapping Swarm Intelligence Soft Computing. 19: 981-1001. DOI: https://doi.org/10.1007/s00500-014-1310-0 |
0.315 |
|
2015 |
Sturlaugson L, Sheppard JW. Sensitivity Analysis of Continuous Time Bayesian Network Reliability Models Journal of Uncertainty Quantification. 3: 346-369. DOI: 10.1137/140953848 |
0.736 |
|
2015 |
Perreault L, Wittie MP, Sheppard J. Communication-aware distributed PSO for dynamic robotic search Ieee Ssci 2014 - 2014 Ieee Symposium Series On Computational Intelligence - Sis 2014: 2014 Ieee Symposium On Swarm Intelligence, Proceedings. 65-72. DOI: 10.1109/SIS.2014.7011777 |
0.213 |
|
2015 |
King H, Fortier N, Sheppard JW. An AI-ESTATE conformant interface for net-centric diagnostic and prognostic reasoning Ieee Instrumentation and Measurement Magazine. 18: 18-24. DOI: 10.1109/Mim.2015.7155768 |
0.739 |
|
2015 |
Mitchell B, Tosun H, Sheppard J. Deep learning using partitioned data vectors Proceedings of the International Joint Conference On Neural Networks. 2015. DOI: 10.1109/IJCNN.2015.7280484 |
0.215 |
|
2015 |
Perreault L, Thornton M, Strasser S, Sheppard JW. Deriving prognostic continuous time Bayesian networks from D-matrices Autotestcon (Proceedings). 2015: 152-161. DOI: 10.1109/AUTEST.2015.7356482 |
0.463 |
|
2014 |
Donnelly PJ, Sheppard JW. Classification of Monophonic Musical Instruments Using Bayesian Networks Computer Music Journal. 37: 70-86. DOI: https://doi.org/10.1162/COMJ_a_00210 |
0.307 |
|
2014 |
Perreault L, Sheppard J, King H, Sturlaugson L. Using continuous-time Bayesian networks for standards-based diagnostics and prognostics Autotestcon (Proceedings). 198-204. DOI: 10.1109/AUTEST.2014.6935145 |
0.371 |
|
2014 |
Wang C, Miller CJ, Nehrir MH, Sheppard JW, McElmurry SP. A load profile management integrated power dispatch using a Newton-like particle swarm optimization method Sustainable Computing: Informatics and Systems. DOI: 10.1016/J.Suscom.2014.10.001 |
0.413 |
|
2014 |
Tosun H, Sheppard JW. Training restricted Boltzmann machines with overlapping partitions Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 8726: 195-208. DOI: 10.1007/978-3-662-44845-8_13 |
0.298 |
|
2013 |
Donnelly PJ, Sheppard JW. Classification of Musical Timbre Using Bayesian Networks Computer Music Journal. 37: 70-86. DOI: 10.1162/Comj_A_00210 |
0.658 |
|
2013 |
Schuh M, Sheppard J, Strasser S, Angryk R, Izurieta C. An IEEE standards-based visualization tool for knowledge discovery in maintenance event sequences Ieee Aerospace and Electronic Systems Magazine. 28: 30-39. DOI: 10.1109/Maes.2013.6559379 |
0.726 |
|
2013 |
Strasser S, Sheppard J. Diagnostic model maturation Ieee Aerospace and Electronic Systems Magazine. 28: 34-43. DOI: 10.1109/Maes.2013.6470443 |
0.761 |
|
2013 |
Sturlaugson LE, Sheppard JW. Principal component analysis preprocessing with Bayesian networks for battery capacity estimation Conference Record - Ieee Instrumentation and Measurement Technology Conference. 98-101. DOI: 10.1109/I2MTC.2013.6555389 |
0.357 |
|
2013 |
Sturlaugson L, Fortier N, Donnelly P, Sheppard JW. Implementing AI-ESTATE with prognostic extensions in Java Autotestcon (Proceedings). 306-313. DOI: 10.1109/AUTEST.2013.6645086 |
0.67 |
|
2013 |
Ryhajlo N, Sturlaugson L, Sheppard JW. Diagnostic Bayesian networks with fuzzy evidence Autotestcon (Proceedings). 242-249. DOI: 10.1109/AUTEST.2013.6645075 |
0.439 |
|
2012 |
Berwald J, Gedeon T, Sheppard J. Using Machine Learning to Predict Catastrophes in Dynamical Systems Journal of Applied Computational Mathematics. 236: 2235-2245. DOI: https://doi.org/10.1016/j.cam.2011.11.006 |
0.228 |
|
2012 |
Haberman B, Sheppard JW. Overlapping Particle Swarms for Energy-Efficient Routing in Sensor Networks Wireless Networks. 18: 351-363. DOI: https://doi.org/10.1007/s11276-011-0404-1 |
0.244 |
|
2012 |
Fortier N, Sheppard JW, Pillai KG. DOSI: Training artificial neural networks using overlapping swarm intelligence with local credit assignment 6th International Conference On Soft Computing and Intelligent Systems, and 13th International Symposium On Advanced Intelligence Systems, Scis/Isis 2012. 1420-1425. DOI: 10.1109/SCIS-ISIS.2012.6505078 |
0.362 |
|
2012 |
Pillai KG, Sheppard JW. Abductive inference in Bayesian belief networks using swarm intelligence 6th International Conference On Soft Computing and Intelligent Systems, and 13th International Symposium On Advanced Intelligence Systems, Scis/Isis 2012. 375-380. DOI: 10.1109/SCIS-ISIS.2012.6505074 |
0.391 |
|
2012 |
Donnelly PJ, Sturlaugson LE, Sheppard JW. A standards-based approach to gray-scale health assessment using fuzzy fault trees Autotestcon (Proceedings). 174-181. DOI: 10.1109/AUTEST.2012.6334529 |
0.644 |
|
2012 |
Berwald J, Gedeon T, Sheppard J. Using machine learning to predict catastrophes in dynamical systems Journal of Computational and Applied Mathematics. 236: 2235-2245. DOI: 10.1016/J.Cam.2011.11.006 |
0.401 |
|
2012 |
Haberman BK, Sheppard JW. Overlapping particle swarms for energy-efficient routing in sensor networks Wireless Networks. 18: 351-363. DOI: 10.1007/S11276-011-0404-1 |
0.397 |
|
2011 |
Pillai KG, Sheppard JW. Overlapping swarm intelligence for training artificial neural networks Ieee Ssci 2011 - Symposium Series On Computational Intelligence - Sis 2011: 2011 Ieee Symposium On Swarm Intelligence. 213-220. DOI: 10.1109/SIS.2011.5952566 |
0.344 |
|
2011 |
Tosun H, Sheppard JW. Incorporating evidence into trust propagation models using Markov Random Fields 2011 Ieee International Conference On Pervasive Computing and Communications Workshops, Percom Workshops 2011. 263-269. DOI: 10.1109/PERCOMW.2011.5766880 |
0.371 |
|
2011 |
Schuh M, Sheppard J, Strasser S, Angryk R, Izurieta C. Ontology-guided knowledge discovery of event sequences in maintenance data Autotestcon (Proceedings). 279-285. DOI: 10.1109/AUTEST.2011.6058745 |
0.314 |
|
2011 |
Strasser S, Sheppard J, Schuh M, Angryk R, Izurieta C. Graph-based ontology-guided data mining for D-matrix model maturation Ieee Aerospace Conference Proceedings. DOI: 10.1109/AERO.2011.5747579 |
0.443 |
|
2010 |
Sheppard JW, Butcher SGW, Donnelly PJ. Demonstrating semantic interoperability of diagnostic reasoners via AI-ESTATE Ieee Aerospace Conference Proceedings. DOI: 10.1109/AERO.2010.5446837 |
0.597 |
|
2009 |
Choi K, Singh S, Kodali A, Pattipati K, Sheppard JW, Namburu S, Chigusa S, Prokhorov D, Qiao L. Novel Classifier Fusion Approaches for Fault Diagnosis in Automotive Systems Ieee Transactions On Instrumentation and Measurement. 58: 602-611. DOI: https://doi.org/10.1109/TIM.2008.2004340 |
0.324 |
|
2009 |
Butcher SGW, Sheppard JW. Distributional smoothing in bayesian fault diagnosis Ieee Transactions On Instrumentation and Measurement. 58: 342-349. DOI: 10.1109/TIM.2008.928874 |
0.31 |
|
2009 |
Butcher SGW, Sheppard JW. Distributional Smoothing in Bayesian Fault Diagnosis Ieee Transactions On Instrumentation and Measurement. 58: 342-349. DOI: 10.1109/Tim.2008.928874 |
0.73 |
|
2009 |
Sheppard J. Special Section on the 2007 IEEE AUTOTESTCON Ieee Transactions On Instrumentation and Measurement. 58: 238-239. DOI: 10.1109/Tim.2008.2005945 |
0.381 |
|
2009 |
Choi K, Singh A, Kodali A, Pattipati KR, Sheppard JW, Namburu SM, Chigusa S, Prokhorov DV, Qiao L. Novel classifier fusion approaches for fault diagnosis in automotive systems Ieee Transactions On Instrumentation and Measurement. 58: 602-611. DOI: 10.1109/TIM.2008.2004340 |
0.354 |
|
2009 |
Sheppard JW, Kaufman MA, Wilmer TJ. IEEE Standards for Prognostics and Health Management Ieee Aerospace and Electronic Systems Magazine. 24: 34-41. DOI: 10.1109/Maes.2009.5282287 |
0.385 |
|
2009 |
Sheppard JW, Butcher SGW, Donnelly PJ. Standard diagnostic services for the ATS framework Autotestcon (Proceedings). 393-400. DOI: 10.1109/AUTEST.2009.5314012 |
0.593 |
|
2009 |
Sheppard JW, Butcher SGW, Donnelly PJ, Mitchell BR. Demonstrating semantic interoperability of diagnostic models via AI-ESTATE Ieee Aerospace Conference Proceedings. DOI: 10.1109/AERO.2009.4839685 |
0.625 |
|
2007 |
Choi K, Singh S, Kodali A, Pattipati KR, Sheppard JW, Namburu SM, Chigusa S, Prokhorov DV, Qiao L. Novel classifier fusion approahces for fault diagnosis in automotive systems Autotestcon (Proceedings). 260-269. DOI: 10.1109/Tim.2008.2004340 |
0.443 |
|
2007 |
Martin SR, Wright SE, Sheppard JW. Offline and online evolutionary bi-directional RRT algorithms for efficient re-planning in dynamic environments Proceedings of the 3rd Ieee International Conference On Automation Science and Engineering, Ieee Case 2007. 1131-1136. DOI: 10.1109/COASE.2007.4341761 |
0.345 |
|
2007 |
Sheppard JW, Butcher SGW. A Formal Analysis of Fault Diagnosis with DMatrices Journal of Electronic Testing: Theory and Applications. 23: 309-322. DOI: 10.1007/S10836-006-0628-7 |
0.436 |
|
2007 |
Sheppard JW, Butcher SGW. A formal analysis of fault diagnosis with D-matrices Journal of Electronic Testing: Theory and Applications (Jetta). 23: 309-322. DOI: 10.1007/s10836-006-0628-7 |
0.335 |
|
2005 |
Sheppard JW, Kaufman MA. A Bayesian Approach to Diagnostics and Prognostics from Built In Test Ieee Transactions On Instrumentation and Measurement. 54: 1003-1018. DOI: https://doi.org/10.1109/TIM.2005.847351 |
0.295 |
|
2005 |
Sheppard JW, Kaufman MA. A Bayesian approach to diagnosis and prognosis using built-in test Ieee Transactions On Instrumentation and Measurement. 54: 1003-1018. DOI: 10.1109/Tim.2005.847351 |
0.452 |
|
1998 |
Sheppard JW, Simpson WR. Managing conflict in system diagnosis Computer. 31: 69-76. DOI: 10.1109/2.660192 |
0.433 |
|
1998 |
Shombert LA, Sheppard JW. A Behavior Model for Next Generation Test Systems Journal of Electronic Testing, Theory and Applications. 13: 299-314. DOI: 10.1023/A:1008337903968 |
0.41 |
|
1998 |
Sheppard JW. Machine Learning. 33: 201-233. DOI: 10.1023/A:1007566607659 |
0.383 |
|
1997 |
Sheppard J. System Test Standards Committee Ieee Design & Test of Computers. 14: 89-90. DOI: 10.1109/Mdt.1997.573376 |
0.349 |
|
1997 |
Sheppard JW, Salzberg SL. Artificial Intelligence Review. 11: 343-370. DOI: 10.1023/A:1006597715165 |
0.572 |
|
1996 |
Sheppard JW. SCC20 attracts IEC participation Ieee Design & Test of Computers. 13: 2. DOI: 10.1109/Mdt.1996.10000 |
0.275 |
|
1995 |
Sheppard J. SCC20 to work with IEC Ieee Design & Test of Computers. 12: 10. DOI: 10.1109/MDT.1995.466363 |
0.206 |
|
1993 |
Sheppard JW, Simpson WR. Performing Effective Fault Isolation in Integrated Diagnostics Ieee Design and Test of Computers. 10: 78-90. DOI: 10.1109/54.211532 |
0.43 |
|
1993 |
Simpson WR, Sheppard JW. Fault Isolation in an Integrated Diagnostic Environment Ieee Design and Test of Computers. 10: 52-66. DOI: 10.1109/54.199805 |
0.443 |
|
1992 |
Simpson WR, Sheppard JW. System perspectwe on diagnostic testing Proceedings - International Test Conference. 1992: 547. DOI: 10.1109/TEST.1992.527868 |
0.261 |
|
1992 |
Sheppard JW, Simpson WR. Applying testability analysis for integrated diagnostics Ieee Design and Test of Computers. 9: 65-78. DOI: 10.1109/54.156160 |
0.435 |
|
1992 |
Simpson WR, Sheppard JW. System Testability Assessment for Integrated Diagnostics Ieee Design and Test of Computers. 9: 40-54. DOI: 10.1109/54.124516 |
0.423 |
|
1991 |
Simpson WR, Sheppard JW. System Complexity and Integrated Diagnostics Ieee Design and Test of Computers. 8: 16-30. DOI: 10.1109/54.84239 |
0.44 |
|
1991 |
Sheppard JW, Simpson WR. A Mathematical Model for Integrated Diagnostics Ieee Design and Test of Computers. 8: 25-38. DOI: 10.1109/54.107203 |
0.468 |
|
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