| A lexical approach for classifying malicious URLs M Darling, G Heileman, G Gressel, A Ashok, P Poornachandran 2015 international conference on high performance computing & simulation …, 2015 | 97 | 2015 |
| Intelligent modeling for nuclear power plant accident management MC Darling, GF Luger, TB Jones, MR Denman, KM Groth International Journal on Artificial Intelligence Tools 27 (02), 1850003, 2018 | 36 | 2018 |
| Building and using dynamic risk-informed diagnosis procedures for complex system accidents KM Groth, MR Denman, MC Darling, TB Jones, GF Luger Proceedings of the Institution of Mechanical Engineers, Part O: Journal of …, 2020 | 27 | 2020 |
| A Dynamic Bayesian Network for Diagnosing Nuclear Power Plant Accidents. TB Jones, MC Darling, KM Groth, MR Denman, GF Luger FLAIRS, 179-184, 2016 | 21 | 2016 |
| Feature importance guided attack: A model agnostic adversarial attack G Gressel, N Hegde, A Sreekumar, R Radhakrishnan, K Harikumar, ... arXiv preprint arXiv:2106.14815, 2021 | 17 | 2021 |
| Uncertainty quantification for machine learning DJ Stracuzzi, MG Chen, MC Darling, MG Peterson, C Vollmer Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2017 | 17 | 2017 |
| Quantifying uncertainty to improve decision making in machine learning DJ Stracuzzi, MC Darling, MG Peterson, MG Chen Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 14 | 2018 |
| Data-driven uncertainty quantification for multisensor analytics DJ Stracuzzi, MC Darling, MG Chen, MG Peterson Ground/Air Multisensor Interoperability, Integration, and Networking for …, 2018 | 14 | 2018 |
| Toward uncertainty quantification for supervised classification MC Darling, DJ Stracuzzi Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 13 | 2018 |
| Using uncertainty to interpret supervised machine learning predictions MC Darling | 9 | 2019 |
| Proof-of-concept accident diagnostic support for sodium fast reactors. KM Groth, MR Denman, TB Jones, M Darling, GF Luger Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2015 | 7 | 2015 |
| ALADDIN: The automatic loader of accident data for dynamic inferencing networks MC Darling, TB Jones, GF Luger, KM Groth SAND2015-10401, Sandia National Laboratories, Albuquerque, NM, 2015 | 4 | 2015 |
| Using uncertainty as a defense against adversarial attacks for tabular datasets P Santhosh, G Gressel, MC Darling Australasian Joint Conference on Artificial Intelligence, 719-732, 2022 | 2 | 2022 |
| A decision theoretic approach to optimizing machine learning decisions with prediction uncertainty RV Field Jr, MC Darling Sandia National Lab.(SNL-NM), Albuquerque, NM (United States); Sandia …, 2022 | 2 | 2022 |
| ADAPT J Reynolds, Z Jankovsky, KG Metzroth, M Darling Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 2 | 2018 |
| Uncertainty in Data Analytics. DJ Stracuzzi, MG Chen, MC Darling, SM Dauphin, MG Peterson, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2016 | 2 | 2016 |
| Preliminary Results on Applying Nonparametric Clustering and Bayesian Consensus Clustering Methods to Multimodal Data MG Chen, MC Darling, DJ Stracuzzi Sandia National Lab.(SNL-CA), Livermore, CA (United States); Sandia National …, 2018 | 1 | 2018 |
| A Mathematical Framework for Uncertainty Quantification in Multimodal Image Analysis via Probabilistic Clustering Models. MG Chen, DJ Stracuzzi, MC Darling Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2018 | 1 | 2018 |
| Building and using dynamic risk-informed diagnosis procedures for severe accidents KM Groth, MR Denman, MC Darling, TB Jones, GF Luger | 1 | 2017 |
| Improving and Assessing the Quality of Uncertainty Quantification in Deep Learning JR Adams, R Baiyasi, B Berman, MC Darling, T Ganter, F Liang, ... Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2023 | | 2023 |
David J StracuzziSandia National LaboratoriesПотвърден имейл адрес: sandia.gov
