Staff information

PNNL Publications

2024

• Sizemore L., B.J. Hutchinson, and E. Borda. 2024. "Use of Machine Learning to Analyze Chemistry Card Sort Tasks." Chemistry Education Research & Practice 25, no. 2:417-437. PNNL-SA-195093. doi:10.1039/D2RP00029F

2023

• Tully J., R. Haight, B.J. Hutchinson, S. Huang, J. Lee, and S. Katipamula. 2023. "Dilated Causal Convolutional Neural Networks for Forecasting Zone Airflow to Estimate Short-Term Energy Consumption." Energy and Buildings 286. PNNL-ACT-SA-10729. doi:10.1016/j.enbuild.2023.112890

2020

• Ayala A., C. Drazic, B.J. Hutchinson, B.S. Kravitz, and C. Tebaldi. 2020. "Loosely Conditioned Emulation of Global Climate Models With Generative Adversarial Networks." In NeurIPS 2020 Workshop Tackling Climate Change with Machine Learning, December 11, 2020. PNNL-SA-157069.
• 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
• Weber T., A. Corotan, B.J. Hutchinson, B.S. Kravitz, and R.P. Link. 2020. "Technical Note: Deep Learning for Creating Surrogate Models of Precipitation in Earth System Models." Atmospheric Chemistry and Physics 20, no. 4:2303-2317. PNNL-SA-141681. doi:10.5194/acp-20-2303-2020

2019

• Puchko A.V., R.P. Link, B.J. Hutchinson, A.C. Snyder, and B.S. Kravitz. 2019. "DeepClimGAN: A High-Resolution Climate Data Generator." In NeurIPS 2019 Workshop Tackling Climate Change with Machine Learning, December 14, 2019, Vancouver BC. PNNL-SA-147276.
• Roberts G., S. Haile, R. Sainju, D.J. Edwards, B.J. Hutchinson, and Y. Zhu. 2019. "Deep Learning for Semantic Segmentation of Defects in Advanced STEM Images of Steels." Scientific Reports 9, no. 1:Article No.12744. PNNL-SA-146546. doi:10.1038/s41598-019-49105-0
• Volkova S., E.M. Ayton, D.L. Arendt, Z. Huang, and B.J. Hutchinson. 2019. "Explaining Multimodal Deceptive News Prediction Models." In Proceedings of the Thirteenth International AAAI Conference on Web and Social Media (ICWSM 2019), June 11-14, 2019, Munich, Germany, 659-662. Menlo Park, California:Association for the Advancement of Artificial Intelligence. PNNL-SA-135457.
• Zhu Y., G.W. Roberts, R. Sainju, B.J. Hutchinson, R.J. Kurtz, M.B. Toloczko, and D.J. Edwards, et al. 2019. "ADVANCED-STEM-BASED DEEP LEARNING FOR SEMANTIC SEGMENTATION OF DEFECTS IN STEELS." In Fusion Materials Semiannual Progress Report for the Period Ending December 31, 2018, edited by F.W. Wiffen and S. Melton. 83-84. DOE-ER-0313/65. Oak Ridge, Tennessee:Oak Ridge National Laboratory. PNNL-SA-141280.

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., 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.