Fast-Classifying, High-Accuracy Spiking Deep Networks Through Weight and Threshold Balancing PU Diehl, D Neil, J Binas, M Cook, SC Liu, M Pfeiffer International Joint Conference on Neural Networks (IJCNN), 2015 | 1140 | 2015 |
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences D Neil, M Pfeiffer, SC Liu Advances in Neural Information Processing Systems (NIPS), 2016 29, 2016 | 535 | 2016 |
Real-time classification and sensor fusion with a spiking deep belief network P O'Connor, D Neil, SC Liu, T Delbruck, M Pfeiffer Frontiers in neuroscience 7, 178, 2013 | 529 | 2013 |
Applications of machine learning to diagnosis and treatment of neurodegenerative diseases MA Myszczynska, PN Ojamies, AMB Lacoste, D Neil, A Saffari, R Mead, ... Nature reviews neurology 16 (8), 440-456, 2020 | 454 | 2020 |
Minitaur, an event-driven FPGA-based spiking network accelerator D Neil, SC Liu IEEE transactions on very large scale integration (VLSI) systems 22 (12 …, 2014 | 270 | 2014 |
DDD17: End-to-end DAVIS driving dataset J Binas, D Neil, SC Liu, T Delbruck arXiv preprint arXiv:1711.01458, 2017 | 215 | 2017 |
2015 International Joint Conference on Neural Networks (IJCNN) PU Diehl, D Neil, J Binas, M Cook, SC Liu, M Pfeiffer International Joint Conference on Neural Networks (IJCNN), 2015 | 212 | 2015 |
DeltaRNN: A power-efficient recurrent neural network accelerator C Gao, D Neil, E Ceolini, SC Liu, T Delbruck Proceedings of the 2018 ACM/SIGDA International Symposium on Field …, 2018 | 168 | 2018 |
Robustness of spiking deep belief networks to noise and reduced bit precision of neuro-inspired hardware platforms E Stromatias, D Neil, M Pfeiffer, F Galluppi, SB Furber, SC Liu Frontiers in neuroscience 9, 222, 2015 | 139 | 2015 |
Steering a predator robot using a mixed frame/event-driven convolutional neural network DP Moeys, F Corradi, E Kerr, P Vance, G Das, D Neil, D Kerr, T Delbrück 2016 Second international conference on event-based control, communication …, 2016 | 130 | 2016 |
Feature representations for neuromorphic audio spike streams J Anumula, D Neil, T Delbruck, SC Liu Frontiers in neuroscience 12, 23, 2018 | 110 | 2018 |
Effective Sensor Fusion with Event-Based Sensors and Deep Network Architectures D Neil, SC Liu IEEE Int. Symposium on Circuits and Systems (ISCAS), 2016 | 105 | 2016 |
Scalable Energy-Efficient, Low-Latency Implementations of Spiking Deep Belief Networks on SpiNNaker E Stromatias, D Neil, F Galluppi, M Pfeiffer, SC Liu, S Furber IEEE International Joint Conference on Neural Networks (IJCNN), 2015 | 103* | 2015 |
A curriculum learning method for improved noise robustness in automatic speech recognition S Braun, D Neil, SC Liu 2017 25th European Signal Processing Conference (EUSIPCO), 548-552, 2017 | 102 | 2017 |
Combined frame- and event-based detection and tracking H Liu, DP Moeys, D Neil, SC Liu, T Delbruck IEEE Int. Symposium on Circuits and Systems (ISCAS), 2016 | 100 | 2016 |
Learning to be Efficient: Algorithms for Training Low-Latency, Low-Compute Deep Spiking Neural Networks D Neil, M Pfeiffer, SC Liu ACM Symposium on Applied Computing 31, 2016 | 93 | 2016 |
Exploring deep recurrent models with reinforcement learning for molecule design D Neil, M Segler, L Guasch, M Ahmed, D Plumbley, M Sellwood, N Brown | 84 | 2018 |
Ddd20 end-to-end event camera driving dataset: Fusing frames and events with deep learning for improved steering prediction Y Hu, J Binas, D Neil, SC Liu, T Delbruck 2020 IEEE 23rd International Conference on Intelligent Transportation …, 2020 | 77 | 2020 |
Delta networks for optimized recurrent network computation D Neil, JH Lee, T Delbruck, SC Liu International conference on machine learning, 2584-2593, 2017 | 72 | 2017 |
Interpretable Graph Convolutional Neural Networks for Inference on Noisy Knowledge Graphs D Neil, J Briody, A Lacoste, A Sim, P Creed, A Saffari Proceedings of the Machine Learning for Health (ML4H) Workshop at NeurIPS 2018, 2018 | 42 | 2018 |