| Towards synaptic behavior of nanoscale reram devices for neuromorphic computing applications K Beckmann, W Olin-Ammentorp, G Chakma, S Amer, GS Rose, C Hobbs, ... ACM Journal on Emerging Technologies in Computing Systems (JETC) 16 (2), 1-18, 2020 | 17 | 2020 |
| Stochasticity and robustness in spiking neural networks W Olin-Ammentorp, K Beckmann, CD Schuman, JS Plank, NC Cady Neurocomputing 419, 23-36, 2021 | 15 | 2021 |
| Fabrication and performance of hybrid reram-cmos circuit elements for dynamic neural networks M Liehr, J Hazra, K Beckmann, W Olin-Ammentorp, N Cady, R Weiss, ... Proceedings of the International Conference on Neuromorphic Systems, 1-4, 2019 | 14 | 2019 |
| Biologically-inspired neuromorphic computing W Olin-Ammentorp, N Cady Science Progress 102 (3), 261-276, 2019 | 11 | 2019 |
| The effect of reactive ion etch (RIE) process conditions on ReRAM device performance K Beckmann, J Holt, W Olin-Ammentorp, Z Alamgir, J Van Nostrand, ... Semiconductor Science and Technology 32 (9), 095013, 2017 | 10 | 2017 |
| Full CMOS-memristor implementation of a dynamic neuromorphic architecture N Cady, K Beckmann, W Olin-Ammentorp, G Chakma, S Amer, R Weiss, ... GOMACTech Conference, 2018 | 8 | 2018 |
| Impact of etch process on hafnium dioxide based nanoscale RRAM devices K Beckmann, J Holt, W Olin-Ammentorp, J Van Nostrand, N Cady ECS Transactions 75 (13), 93, 2016 | 7 | 2016 |
| A dual-memory architecture for reinforcement learning on neuromorphic platforms W Olin-Ammentorp, Y Sokolov, M Bazhenov Neuromorphic Computing and Engineering 1 (2), 024003, 2021 | 3 | 2021 |
| Applying memristors towards low-power, dynamic learning for neuromorphic applications W Olin-Ammentorp, K Beckmann, JE Van Nostrand, GS Rose, ME Dean, ... 42nd Annual GOMACTech Conference, Reno, NV, 2017 | 3 | 2017 |
| Deep Phasor Networks: Connecting Conventional and Spiking Neural Networks W Olin-Ammentorp, M Bazhenov 2022 International Joint Conference on Neural Networks (IJCNN), 1-10, 2022 | 2 | 2022 |
| Bridge networks: Relating inputs through vector-symbolic manipulations W Olin-Ammentorp, M Bazhenov International Conference on Neuromorphic Systems 2021, 1-6, 2021 | 2 | 2021 |
| Training Spiking Networks via Natural Evolution Strategies W Olin-Ammentorp, N Cady Proceedings of the International Conference on Neuromorphic Systems, 1-6, 2019 | 1 | 2019 |
| Applying non-parametric testing to discrete transfer entropy W Olin-Ammentorp, N Cady bioRxiv, 460733, 2018 | 1 | 2018 |
| Synaptic Behavior of Nanoscale ReRAM Devices for the Implementation in a Dynamic Neural Network Array K Beckmann, W Olin-Ammentorp, S Russell, N Suguitan, C Hobbs, ... 2018 International Integrated Reliability Workshop (IIRW), 1-4, 2018 | 1 | 2018 |
| Investigation of Reactively Sputtered Titanium Oxide Memristors W Olin-Ammentorp Rochester Institute of Technology, 2015 | 1 | 2015 |
| Resistive Transition Metal Oxide Memory W Olin-Ammentorp | 1 | 2015 |
| Hyperdimensional Computing Provides a Programming Paradigm for Oscillatory Systems W Olin-Ammentorp arXiv preprint arXiv:2312.11783, 2023 | | 2023 |
| Sparsifying Spiking Networks through Local Rhythms W Olin-Ammentorp Proceedings of the 2023 International Conference on Neuromorphic Systems, 1-4, 2023 | | 2023 |
| Residual and Attentional Architectures for Vector-Symbols W Olin-Ammentorp Maxim Bazhenov arXiv e-prints, arXiv: 2207.08953, 2022 | | 2022 |
| Cellular Memristive-Output Reservoir (CMOR) W Olin-Ammentorp, K Beckmann, NC Cady arXiv preprint arXiv:1906.06414, 2019 | | 2019 |
Nathaniel C. CadyEmpire Innovation Professor, SUNY Polytechnic InstituteVerified email at sunypoly.edu
