| Cross-Quality Few-Shot Transfer for Alloy Yield Strength Prediction: A New Materials Science Benchmark and A Sparsity-Oriented Optimization Framework X Chen, T Chen, EY Olivares, K Elder, S McCall, A Perron, J McKeown, ... Conference on Parsimony and Learning, 302-323, 2024 | | 2024 |
| INDUSTRIAL CONTROL SYSTEM DEVICE CLASSIFICATION BM Kelley, I Chakraborty, BJ Gallagher, DM Merl US Patent App. 17/860,852, 2023 | | 2023 |
| Cross-Quality Few-Shot Transfer for Alloy Yield Strength Prediction: A New Material Science Benchmark and An Integrated Optimization Framework X Chen, T Chen, EY Olivares, K Elder, SK McCall, APP Perron, ... | | 2022 |
| Explainable machine learning in materials science X Zhong, B Gallagher, S Liu, B Kailkhura, A Hiszpanski, TYJ Han npj Computational Materials 8 (1), 204, 2022 | 97 | 2022 |
| A Strategic Approach to Machine Learning for Material Science: How to Tackle Real-World Challenges and Avoid Pitfalls P Karande, B Gallagher, TYJ Han Chemistry of Materials 34 (17), 7650-7665, 2022 | 19 | 2022 |
| Accurate parameterization of the kinetic energy functional S Kumar, EL Borda, B Sadigh, S Zhu, S Hamel, B Gallagher, V Bulatov, ... The Journal of Chemical Physics 156 (2), 2022 | 7 | 2022 |
| Accurate parameterization of the kinetic energy functional for calculations using exact-exchange S Kumar, B Sadigh, S Zhu, P Suryanarayana, S Hamel, B Gallagher, ... The Journal of Chemical Physics 156 (2), 2022 | 4 | 2022 |
| Device Classification for Industrial Control Systems using Predicted Traffic Features I Chakraborty, BM Kelley, B Gallagher Frontiers in Computer Science, 28, 2022 | 1 | 2022 |
| Industrial control system device classification using network traffic features and neural network embeddings I Chakraborty, BM Kelley, B Gallagher Array 12, 100081, 2021 | 9 | 2021 |
| Explaining neural network predictions of material strength IA Palmer, TN Mundhenk, B Gallagher, Y Han arXiv preprint arXiv:2111.03729, 2021 | 2 | 2021 |
| A study of real-world micrograph data quality and machine learning model robustness X Zhong, B Gallagher, K Eves, E Robertson, TN Mundhenk, TYJ Han npj Computational Materials 7 (1), 161, 2021 | 8 | 2021 |
| Explaining neural network predictions of material strength TN Mundhenk, IA Palmer, BJ Gallagher, Y Han Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2021 | | 2021 |
| Performance Evaluation of Network Flow and Device Classification using Network Features and Device Embeddings I Chakraborty, B Kelley, B Gallagher, D Merl Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2020 | | 2020 |
| Predicting compressive strength of consolidated molecular solids using computer vision and deep learning B Gallagher, M Rever, D Loveland, TN Mundhenk, B Beauchamp, ... Materials & Design 190, 108541, 2020 | 46 | 2020 |
| Nanomaterial synthesis insights from machine learning of scientific articles by extracting, structuring, and visualizing knowledge AM Hiszpanski, B Gallagher, K Chellappan, P Li, S Liu, H Kim, J Han, ... Journal of chemical information and modeling 60 (6), 2876-2887, 2020 | 67 | 2020 |
| Exploiting Spark for HPC Simulation Data: Taming the Ephemeral Data Explosion M Jiang, B Gallagher, A Chu, G Abdulla, T Bender Proceedings of the International Conference on High Performance Computing in …, 2020 | 3 | 2020 |
| Reliable and explainable machine-learning methods for accelerated material discovery B Kailkhura, B Gallagher, S Kim, A Hiszpanski, TYJ Han npj Computational Materials 5 (1), 108, 2019 | 146 | 2019 |
| A deep learning framework for mesh relaxation in arbitrary Lagrangian-Eulerian simulations M Jiang, B Gallagher, N Mandell, A Maguire, K Henderson, G Weinert Applications of Machine Learning 11139, 168-182, 2019 | 6 | 2019 |
| Enabling Data Analytics Workflows using Node-Local Storage TMA Do, M Jiang, B Gallagher, A Chu, C Harrison, K Vahi, E Deelman International Conference for High Performance Computing, Networking, Storage …, 2018 | 3 | 2018 |
| Network structure inference, a survey: Motivations, methods, and applications I Brugere, B Gallagher, TY Berger-Wolf ACM Computing Surveys (CSUR) 51 (2), 1-39, 2018 | 159 | 2018 |
Tina Eliassi-RadProfessor & The Inaugural Joseph E. Aoun Chair, Northeastern University在 eliassi.org 的电子邮件经过验证
