| Trajectory Planning with Deep Reinforcement Learning in High-Level Action Spaces KR Williams, R Schlossman, D Whitten, J Ingram, S Musuvathy, J Pagan, ... IEEE Transactions on Aerospace and Electronic Systems, 2022 | 10 | 2022 |
| Benchmarking Event-Driven Neuromorphic Architectures CM Vineyard, S Green, WM Severa, ÇK Koç Proceedings of the International Conference on Neuromorphic Systems, 1-5, 2019 | 10 | 2019 |
| RAPDARTS: Resource-aware progressive differentiable architecture search S Green, CM Vineyard, R Helinski, CK Koç 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020 | 9 | 2020 |
| Distillation Strategies for Proximal Policy Optimization S Green, CM Vineyard, CK Koç arXiv preprint arXiv:1901.08128, 2019 | 8 | 2019 |
| Visual Diagnostics for Deep Reinforcement Learning Policy Development J Luo, S Green, P Feghali, G Legrady, CK Koç arXiv preprint arXiv:1809.06781, 2018 | 7 | 2018 |
| Impacts of Mathematical Optimizations on Reinforcement Learning Policy Performance S Green, CM Vineyard, CK Koç 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 6 | 2018 |
| Reinforcement Learning and Trustworthy Autonomy J Luo, S Green, P Feghali, G Legrady, ÇK Koç Cyber-Physical Systems Security, 191-217, 2018 | 5 | 2018 |
| Comparing Neural Accelerators & Neuromorphic Architectures - The False Idol of Operations CM Vineyard, M Plagge, S Green Proceedings of the Neuro-inspired Computational Elements Workshop, 1-6, 2020 | 4 | 2020 |
| Memristors Learn to Play S Green, JB Aimone Nature Electronics 2 (3), 96-97, 2019 | 3 | 2019 |
| Equitable Continuous Organizations with Self-Assessed Valuations H Heaton, S Green arXiv preprint arXiv:2203.10644, 2022 | 1 | 2022 |
| Neural Inspired Computation Remote Sensing Platform CM Vineyard, WM Severa, S Green, R Dellana, M Plagge, AJ Hill Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019 | 1 | 2019 |
| Multi-Agent Dynamic Pricing in a Blockchain Protocol Using Gaussian Bandits A Asseman, T Kornuta, A Patel, M Deible, S Green arXiv preprint arXiv:2212.07942, 2022 | | 2022 |
| Machines Learning about Machines - ML for Analysis and Control of HPC Infrastructure F Wang, S Green, K Pedretti, CM Vineyard, AJ Younge Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2020 | | 2020 |
| State Representation Learning for Deep Planning F Wang, S Green, WM Severa Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019 | | 2019 |
| Methods for Efficient Deep Reinforcement Learning S Green University of California, Santa Barbara, 2019 | | 2019 |
| Learned P-States for High Performance Computing. P Feghali, S Green Sandia National Lab.(SNL-CA), Livermore, CA (United States); Sandia National …, 2018 | | 2018 |
| Mathematical Optimizations for Deep Learning S Green, CM Vineyard, ÇK Koç Cyber-Physical Systems Security, 69-92, 2018 | | 2018 |
Craig M. VineyardSandia National LaboratoriesVerified email at sandia.gov
