Few-shot learning with metric-agnostic conditional embeddings N Hilliard, L Phillips, S Howland, A Yankov, CD Corley, NO Hodas arXiv preprint arXiv:1802.04376, 2018 | 188 | 2018 |
Faster fuzzing: Reinitialization with deep neural models N Nichols, M Raugas, R Jasper, N Hilliard arXiv preprint arXiv:1711.02807, 2017 | 39 | 2017 |
Sharkzor: Interactive deep learning for image triage, sort and summary M Pirrung, N Hilliard, A Yankov, N O'Brien, P Weidert, CD Corley, ... arXiv preprint arXiv:1802.05316, 2018 | 14 | 2018 |
Algorithms for procedural dungeon generation N Hilliard, J Salis, H ELAarag Journal of Computing Sciences in Colleges 33 (1), 166-174, 2017 | 11 | 2017 |
SHARKZOR: Human in the loop ML for user-defined image classification M Pirrung, N Hilliard, N O'Brien, A Yankov, CD Corley, NO Hodas Proceedings of the 23rd International Conference on Intelligent User …, 2018 | 6 | 2018 |
Dynamic input structure and network assembly for few-shot learning N Hilliard, NO Hodas, CD Corley arXiv preprint arXiv:1708.06819, 2017 | 5 | 2017 |
Modeling and simulation of scalable flocking with fully autonomous quadrotors C Micklisch, N Hilliard, H ElAarag 2018 International Symposium on Performance Evaluation of Computer and …, 2018 | 2 | 2018 |
Modeling and simulation of fully autonomous quadrotors C Micklisch, N Hilliard, H ElAarag Proceedings of the Communications and Networking Symposium, 1-12, 2018 | 1 | 2018 |
Modeling and simulation of autonomous quadrotor systems and their onboard sensors C Micklisch, N Hilliard, H ElAarag Simulation 97 (3), 195-214, 2021 | | 2021 |