| Exploring traditional and emerging parallel programming models using a proxy application I Karlin, A Bhatele, J Keasler, BL Chamberlain, J Cohen, Z DeVito, ... 2013 IEEE 27th International Symposium on Parallel and Distributed …, 2013 | 255 | 2013 |
| Biological underpinnings for lifelong learning machines D Kudithipudi, M Aguilar-Simon, J Babb, M Bazhenov, D Blackiston, ... Nature Machine Intelligence 4 (3), 196-210, 2022 | 187 | 2022 |
| Sparse coding for n-gram feature extraction and training for file fragment classification F Wang, TT Quach, J Wheeler, JB Aimone, CD James IEEE Transactions on Information Forensics and Security 13 (10), 2553-2562, 2018 | 42 | 2018 |
| Crossing the cleft: communication challenges between neuroscience and artificial intelligence FS Chance, JB Aimone, SS Musuvathy, MR Smith, CM Vineyard, F Wang Frontiers in computational neuroscience 14, 39, 2020 | 25 | 2020 |
| A domain-agnostic approach for characterization of lifelong learning systems MM Baker, A New, M Aguilar-Simon, Z Al-Halah, SMR Arnold, ... Neural Networks 160, 274-296, 2023 | 22 | 2023 |
| Truly heterogeneous hpc: Co-design to achieve what science needs from hpc SG Cardwell, C Vineyard, W Severa, FS Chance, F Rothganger, F Wang, ... Driving Scientific and Engineering Discoveries Through the Convergence of …, 2020 | 21 | 2020 |
| A spike-timing neuromorphic architecture AJ Hill, JW Donaldson, FH Rothganger, CM Vineyard, DR Follett, ... 2017 IEEE International Conference on Rebooting Computing (ICRC), 1-8, 2017 | 16 | 2017 |
| Simulation tool for asynchronous cortical streams (STACS): interfacing with spiking neural networks F Wang Procedia Computer Science 61, 322-327, 2015 | 7 | 2015 |
| Neural Mini-Apps as a Tool for Neuromorphic Computing Insight C Vineyard, S Cardwell, F Chance, S Musuvathy, F Rothganger, ... Proceedings of the 2022 Annual Neuro-Inspired Computational Elements …, 2022 | 4 | 2022 |
| Localization through Grid-basedEncodings on Digital Elevation Models F Wang, C Teeter, S Luca, S Musuvathy, B Aimone Proceedings of the 2022 Annual Neuro-Inspired Computational Elements …, 2022 | 2 | 2022 |
| Acquisition and representation of spatio-temporal signals in polychronizing spiking neural networks F Wang, WM Severa, F Rothganger Proceedings of the 7th Annual Neuro-inspired Computational Elements Workshop …, 2019 | 2 | 2019 |
| Decomposing spiking neural networks with Graphical Neural Activity Threads BH Theilman, F Wang, F Rothganger, JB Aimone arXiv preprint arXiv:2306.16684, 2023 | 1 | 2023 |
| Analysis framework for adaptive spiking neural networks F Wang University of Illinois at Urbana-Champaign, 2014 | 1 | 2014 |
| Explaining Neural Spike Activity for Simulated Bio-plausible Network through Deep Sequence Learning SR Kulkarni, A Tabassum, SH Lim, CD Schuman, BH Theilman, ... 2024 Neuro Inspired Computational Elements Conference (NICE), 1-7, 2024 | | 2024 |
| Scaling neural simulations in STACS F Wang, S Kulkarni, B Theilman, F Rothganger, C Schuman, SH Lim, ... Neuromorphic Computing and Engineering 4 (2), 024002, 2024 | | 2024 |
| Terrain-Relative Navigation with Neuro-Inspired Elevation Encoding K Michaelson, F Wang, R Zanetti 2023 IEEE/ION Position, Location and Navigation Symposium (PLANS), 851-857, 2023 | | 2023 |
| Distributed Compressed Sparse Row Format for Spiking Neural Network Simulation, Serialization, and Interoperability F Wang arXiv preprint arXiv:2304.05587, 2023 | | 2023 |
| Combining Spike Time Dependent Plasticity (STDP) and Backpropagation (BP) for Robust and Data Efficient Spiking Neural Networks (SNN) F Wang, NA Alonso, CM Teeter Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
| Deriving STDP from Backpropagation. C Teeter, F Wang, A Nicholas Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
| Varied Delays in Spiking Neural Networks Support Learning with Conjunctive Temporal Features. F Wang, C Teeter Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
