Staff information

PNNL Publications

2024

• Drgona J., A.R. Tuor, and D.L. Vrabie. 2024. "Learning Constrained Parametric Differentiable Predictive Control Policies With Guarantees." IEEE Transactions on Systems, Man, and Cybernetics: Systems 54, no. 6:3596 - 3607. PNNL-SA-162577. doi:10.1109/TSMC.2024.3368026

2023

• Abhyankar S.G., J. Drgona, A.R. Tuor, and A.J. August. 2023. "Neuro-physical dynamic load modeling using differentiable parametric optimization." In IEEE Power & Energy Society General Meeting (PESGM 2023), July 16-20, 2023, Orlando, FL, 1-5. Piscataway, New Jersey:IEEE. PNNL-SA-179235. doi:10.1109/PESGM52003.2023.10253098
• Drgona J., A.R. Tuor, J.V. Koch, M.R. Shapiro, E. King, and D.L. Vrabie. 2023. Domain Aware Deep-learning Algorithms Integrated with Scientific-computing Technologies (DADAIST). PNNL-34895. Richland, WA: Pacific Northwest National Laboratory. Domain Aware Deep-learning Algorithms Integrated with Scientific-computing Technologies (DADAIST)
• Koch J.V., Z. Chen, A.R. Tuor, J. Drgona, and D.L. Vrabie. 2023. "Structural Inference of Networked Dynamical Systems with Universal Differential Equations." Chaos: An Interdisciplinary Journal of Nonlinear Science 33, no. 2:023103. PNNL-SA-174936. doi:10.1063/5.0109093
• Shaw Cortez W.E., S.S. Vasisht, A.R. Tuor, J. Drgona, and D.L. Vrabie. 2023. "Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles." In 12th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2022), January 4-6, 2023, Canberra, Australia. IFAC-PapersOnline, edited by J. Trumpf and R. Mahony, 56, 228-233. Amsterdam:Elsevier. PNNL-SA-175459. doi:10.1016/j.ifacol.2023.02.039

2022

• Drgona J., A.R. Tuor, S.S. Vasisht, and D.L. Vrabie. 2022. "Dissipative Deep Neural Dynamical Systems." IEEE Open Journal of Control Systems 1. PNNL-SA-174718. doi:10.1109/OJCSYS.2022.3186838
• Drgona J., K. Kis, A.R. Tuor, D.L. Vrabie, and M. Klauco. 2022. "Differentiable Predictive Control: Deep Learning Alternative to Explicit Model Predictive Control for Unknown Nonlinear Systems." Journal of Process Control 116, no. _:80-92. PNNL-SA-162137. doi:10.1016/j.jprocont.2022.06.001
• Drgona J., S. Mukherjee, A.R. Tuor, M. Halappanavar, and D.L. Vrabie. 2022. "Learning Stochastic Parametric Differentiable Predictive Control Policies." In 10th IFAC Symposium on Robust Control Design (ROCOND 2022), August 30 - September 2, 2022, Kyoto, Japan. IFAC-PapersOnLine, 55, 121 - 126. Amsterdam:Elsevier. PNNL-SA-170144. doi:10.1016/j.ifacol.2022.09.334
• King E., J. Drgona, A.R. Tuor, S.G. Abhyankar, C. Bakker, A. Bhattacharya, and D.L. Vrabie. 2022. "Koopman-based Differentiable Predictive Control for the Dynamics-Aware Economic Dispatch Problem." In American Control Conference (ACC 2022), June 8-10, 2022, Atlanta, GA, 2194-2201. Piscataway, New Jersey:IEEE. PNNL-SA-167421. doi:10.23919/ACC53348.2022.9867379
• Mukherjee S., J. Drgona, A.R. Tuor, M. Halappanavar, and D.L. Vrabie. 2022. "Neural Lyapunov Differentiable Predictive Control." In Proceedings of the 61st IEEE Conference on Decision and Control (CDC 2022), December 6-9, 2022, Cancun, Mexico, 2097-2104. Piscataway, New Jersey:IEEE. PNNL-SA-171659. doi:10.1109/CDC51059.2022.9992386
• Rahman A., J. Drgona, A.R. Tuor, and J.F. Strube. 2022. "Neural Ordinary Differential Equations for Nonlinear System Identification." In American Control Conference (ACC 2022), June 8-10, 2022, Atlanta, GA, 3979-3984. Piscataway, New Jersey:IEEE. PNNL-SA-167502. doi:10.23919/ACC53348.2022.9867586
• Shaw Cortez W.E., J. Drgona, A.R. Tuor, M. Halappanavar, and D.L. Vrabie. 2022. "Differentiable Predictive Control with Safety Guarantees: A Control Barrier Function Approach." In Proceedings of the 61th IEEE Conference on Decision and Control (CDC 2022), December 6-9, 2022, Cancun, Mexico, 932-938. Piscataway, New Jersey:IEEE. PNNL-SA-171767. doi:10.1109/CDC51059.2022.9993146

2021

• Drgona J., A.R. Tuor, S.E. Skomski, S.S. Vasisht, and D.L. Vrabie. 2021. "Deep Learning Explicit Differentiable Predictive Control Laws for Buildings." In 7th IFAC Conference on Nonlinear Model Predictive Control, (NMPC 2021), July 11-14, 2021 Bratislava. IFAC-PapersOnLine, edited by G. Pannocchia, et al, 54, 4-19. PNNL-SA-159943. doi:10.1016/j.ifacol.2021.08.518
• Drgona J., A.R. Tuor, V. Chandan, and D.L. Vrabie. 2021. "Physics-constrained Deep Learning of Multi-zone Building Thermal Dynamics." Energy and Buildings 243. PNNL-SA-166470. doi:10.1016/j.enbuild.2021.110992
• Kvinge H.J., Z.D. New, N.C. Courts, J.H. Lee, L.A. Phillips, C.D. Corley, and A.R. Tuor, et al. 2021. "Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning." In AAAI Workshop on Meta-Learning and MetaDL Challenge, February 9, 2021, Virtual, Online. Proceedings of Machine Learning Research, edited by I. Guyon, et al, 140, 77-89. Brookline, Massachusetts:ML Research Press. PNNL-SA-158201.
• Larson K.B., and A.R. Tuor. 2021. "Deep learning classification of cheatgrass invasion in the Western United States using biophysical and remote sensing data." Remote Sensing 13, no. 7:Article No. 1246. PNNL-SA-159598. doi:10.3390/rs13071246
• Skomski E., S.S. Vasisht, C.L. Wight, A.R. Tuor, J. Drgona, and D.L. Vrabie. 2021. "Constrained Block Nonlinear Neural Dynamical Models." In Proceedings of the American Control Conference (ACC 2021), May 25-28, 2021, Virtual, New Orleans, LA, 2021, 3993 - 4000. Piscataway, New Jersey:IEEE. PNNL-SA-156893. doi:10.23919/ACC50511.2021.9482930
• Skomski S.E., J. Drgona, and A.R. Tuor. 2021. "Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution." In Proceedings of the 3rd Conference on Learning for Dynamics and Control, June 7-8, 2021, edited by A. Jababaie, et al, 144, 980--991. Brookline, Massachusetts:ML Research Press. PNNL-SA-158080.

2020

• Drgona J., A.R. Tuor, V. Chandan, and D.L. Vrabie. 2020. "Physics-constrained Deep Recurrent Neural Models of Building Thermal Dynamics." In Conference on Neural Information Processing Systems (NeurIPS 2020), Workshop Tackling Climate Change with Machine Learning, December 11, 2020, Virtual. San Diego, California:Neural Information Processing Systems Foundation, Inc. PNNL-SA-156966.
• Skomski S.E., A.R. Tuor, A. Avila, L.A. Phillips, Z.D. New, H.J. Kvinge, and C.D. Corley, et al. 2020. "Prototypical Region Proposal Networks for Few-Shot Localization and Classification." In 4th Workshop on Meta-Learning at NeurIPS 2020, December 11, 2020, (Virtual Only). San Diego, California:Neural Information Processing Systems. PNNL-SA-158131.
• Truong L.T., C.A. Jones, B.J. Hutchinson, A. August, B.L. Praggastis, R.J. Jasper, and N.M. Nichols, et al. 2020. "Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW 2020), June 14-19, 2020, Seattle, WA, 3422-3431. Piscataway, New Jersey:IEEE. PNNL-SA-152069. doi:10.1109/CVPRW50498.2020.00402

2018

• Brown A., B.J. Hutchinson, A.R. Tuor, and N.M. Nichols. 2018. "Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection." In Proceedings of the 1st Workshop on Machine Learning for Computing Systems (MLCS 2018), June 12, 2018, Tempe, AZ, Paper No. 1. New York, New York:ACM. PNNL-SA-133000. doi:10.1145/3217871.3217872
• Olney R., A.R. Tuor, F. Jagodzinski, and B.J. Hutchinson. 2018. "Protein Mutation Stability Ternary Classification using Neural Networks and Rigidity Analysis." In 10th International Conference on Bioinformatics and Computational Biology (BICOB 2018), March 19-21, 2018, Las Vegas, NV, edited by A.M. Al-Mubaid, O. Eulenstein and Q. Ding. Winona, Minnesota:The International Society for Computers and Their Applications (ISCA). PNNL-SA-132051.
• Tuor A.R., L.E. Charles, and F. Anubhav. 2018. "Multiple Document Representations from News Alerts for Automated Bio-surveillance Event Detection." In 5th Pacific Northwest Regional NLP Workshop: NW-NLP 2018, April 27, 2018, Redmond, WA, Paper No. arXiv:1902.06231. Stroudsburg, Pennsylvania:Association for Computational Linguistics. PNNL-SA-131548. doi:10.48550/arXiv.1902.06231
• Tuor A.R., R. Baerwolf, N. Knowles, B.J. Hutchinson, N.M. Nichols, and R.J. Jasper. 2018. "Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection." In Proceedings of the 32nd AAAI Conference on Artificial Intelligence, Workshop for Artificial Intelligence for Cyber Security (AICS 2018), February 2-7, 2018, New Orleans, LA, Paper No. arXiv:1712.00557. Palo Alto, California:Association for the Advancement of Artificial Intelligence. PNNL-SA-130482.
• Tuor A.R., S.P. Kaplan, B.J. Hutchinson, N.M. Nichols, and S.M. Robinson. 2018. "Deep Learning for Unsupervised Insider Threat Detection in Structured Cyber Security Data Streams." In Artificial Intelligence for Cyber Security Workshop (AAAI-2017), February 4-5, 2017, San Francisco, CA, 224-231. Palo Alto, California:AAAI Press. PNNL-SA-122883.

2017

• Tuor A.R., S.P. Kaplan, B.J. Hutchinson, N.M. Nichols, and S.M. Robinson. 2017. "Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams." In The AAAI Workshop on Artificial Intelligence for Cyber Security, 224-231; WS-17-04. Palo Alto, California:Association for the Advancement of Artificial Intelligence. PNNL-SA-122088.
• Tuor A.R., S.P. Kaplan, B.J. Hutchinson, N.M. Nichols, and S.M. Robinson. 2017. "Deep Learning for Unsupervised Insider Threat Detection in Structured Cybersecurity Data Streams." In The AAAI-17 Workshop on Artificial Intelligence for Cyber Security (AICS 2017), February 4-9, 2017, San Francisco, CA. Palo Alto, California:Association for the Advancement of Artificial Intelligence. PNNL-SA-122382.