BindsNET: A machine learning-oriented spiking neural networks library in Python H Hazan, DJ Saunders, H Khan, D Patel, DT Sanghavi, HT Siegelmann, ... Frontiers in neuroinformatics 12, 89, 2018 | 291 | 2018 |
Improved robustness of reinforcement learning policies upon conversion to spiking neuronal network platforms applied to Atari Breakout game D Patel, H Hazan, DJ Saunders, H Siegelmann, R Kozma Neural Networks 120, 108-115, 2019 | 76 | 2019 |
Locally connected spiking neural networks for unsupervised feature learning DJ Saunders, D Patel, H Hazan, HT Siegelmann, R Kozma Neural Networks 119, 332-340, 2019 | 60 | 2019 |
Strategy and benchmark for converting deep q-networks to event-driven spiking neural networks W Tan, D Patel, R Kozma Proceedings of the AAAI conference on artificial intelligence 35 (11), 9816-9824, 2021 | 33 | 2021 |
Optimization methods for improved efficiency and performance of Deep Q-Networks upon conversion to neuromorphic population platforms W Tan, R Kozma, D Patel Knowledge-Based Systems 241, 108257, 2022 | 4 | 2022 |
Unsupervised Features Extracted using Winner-Take-All Mechanism Lead to Robust Image Classification D Patel, R Kozma 2020 International Joint Conference on Neural Networks (IJCNN), 1-7, 2020 | 3 | 2020 |
Temporally Layered Architecture for Adaptive, Distributed and Continuous Control D Patel, J Russell, F Walsh, T Rahman, T Sejnowski, H Siegelmann arXiv preprint arXiv:2301.00723, 2022 | 1 | 2022 |
Automatic transpiler that efficiently converts digital circuits to a neural network representation D Patel, I Gavier, J Russell, A Malinsky, E Rietman, H Siegelmann 2022 International Joint Conference on Neural Networks (IJCNN), 01-08, 2022 | 1 | 2022 |
Temporally Layered Architecture for Efficient Continuous Control D Patel, T Sejnowski, H Siegelmann arXiv preprint arXiv:2305.18701, 2023 | | 2023 |
Neural Network Compiler for Parallel High-Throughput Simulation of Digital Circuits I Gavier, J Russell, D Patel, E Rietman, H Siegelmann 2023 IEEE International Parallel and Distributed Processing Symposium (IPDPS …, 2023 | | 2023 |
QuickNets: Saving Training and Preventing Overconfidence in Early-Exit Neural Architectures D Patel, H Siegelmann arXiv preprint arXiv:2212.12866, 2022 | | 2022 |
Playing Atari using Spiking Neural Networks D Patel | | |