| 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 | 337 | 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 | 102 | 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 | 70 | 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 | 46 | 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 | 6 | 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 | 4 | 2020 |
| Optimizing Attention and Cognitive Control Costs Using Temporally Layered Architectures D Patel, T Sejnowski, H Siegelmann Neural Computation 36 (12), 2734-2763, 2024 | 2* | 2024 |
| 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 | 2 | 2023 |
| 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 | 2 | 2022 |
| 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 |
| Quicknets: Saving training and preventing overconfidence in early-exit neural architectures D Patel, H Siegelmann arXiv preprint arXiv:2212.12866, 2022 | 1 | 2022 |
| Navigating the unknown: Leveraging self-information and diversity in partially observable environments D Patel, HT Siegelmann Biochemical and Biophysical Research Communications 741, 150923, 2024 | | 2024 |
| Overcoming Slow Decision Frequencies in Continuous Control: Model-Based Sequence Reinforcement Learning for Model-Free Control D Patel, H Siegelmann arXiv preprint arXiv:2410.08979, 2024 | | 2024 |
| Achieving Precise Control with Slow Hardware: Model-Based Reinforcement Learning for Action Sequence Learning D Patel, HT Siegelmann | | 2024 |
| Optimizing Neural Network Representations of Boolean Networks J Russell, I Gavier, D Patel, E Rietman, HT Siegelmann The Thirteenth International Conference on Learning Representations, 0 | | |
| Playing Atari using Spiking Neural Networks D Patel | | |
Hava SiegelmannProfessor of Computer Science, and Brain Sciences, UMass AmherstПідтверджена електронна адреса в cs.umass.edu
