| Hybrid macro/micro level backpropagation for training deep spiking neural networks Y Jin, W Zhang, P Li Advances in Neural Information Processing Systems, 31, 7005-7015. (2018), 2018 | 222 | 2018 |
| Temporal spike sequence learning via backpropagation for deep spiking neural networks W Zhang, P Li Advances in Neural Information Processing Systems, 2020, 2020 | 211 | 2020 |
| Spike-train level backpropagation for training deep recurrent spiking neural networks W Zhang, P Li Advances in neural information processing systems, 2019, 2019 | 131 | 2019 |
| Spike-train level direct feedback alignment: Sidestepping backpropagation for on-chip training of spiking neural nets J Lee, R Zhang, W Zhang, Y Liu, P Li Frontiers in neuroscience 14, 143, 2020 | 24 | 2020 |
| Information-theoretic intrinsic plasticity for online unsupervised learning in spiking neural networks W Zhang, P Li Frontiers in neuroscience 13, 420224, 2019 | 24 | 2019 |
| Backpropagated neighborhood aggregation for accurate training of spiking neural networks Y Yang, W Zhang, P Li International Conference on Machine Learning, 11852-11862, 2021 | 21 | 2021 |
| Skip-Connected Self-Recurrent Spiking Neural Networks with Joint Intrinsic Parameter and Synaptic Weight Training W Zhang, P Li Neural Computation, 1886-1913, 2021 | 17 | 2021 |
| Parallel time batching: Systolic-array acceleration of sparse spiking neural computation JJ Lee, W Zhang, P Li 2022 IEEE International Symposium on High-Performance Computer Architecture …, 2022 | 16 | 2022 |
| Boosting throughput and efficiency of hardware spiking neural accelerators using time compression supporting multiple spike codes C Xu, W Zhang, Y Liu, P Li Frontiers in neuroscience 14, 498784, 2020 | 16 | 2020 |
| Spiking neural networks with laterally-inhibited self-recurrent units W Zhang, P Li 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 9 | 2021 |
| Robust deep multi-modal sensor fusion using fusion weight regularization and target learning MS Shim, C Zhao, Y Li, X Zhang, W Zhang, P Li arXiv preprint arXiv:1901.10610, 2019 | 9 | 2019 |
| Composing Recurrent Spiking Neural Networks using Locally-Recurrent Motifs and Risk-Mitigating Architectural Optimization W Zhang, H Geng, P Li arXiv preprint arXiv:2108.01793, 2021 | 6 | 2021 |
| Enabling non-Hebbian learning in recurrent spiking neural processors with hardware-friendly on-chip intrinsic plasticity Y Liu, W Zhang, P Li IEEE Journal on Emerging and Selected Topics in Circuits and Systems 9 (3 …, 2019 | 6 | 2019 |
| Multiple linear regression haze-removal model based on dark channel prior B Li, W Zhang, M Lu 2018 International Conference on Computational Science and Computational …, 2018 | 6 | 2018 |
| Convergence-boosted graph partitioning using maximum spanning trees for iterative solution of large linear circuits Y Wang, W Zhang, P Li, J Gong Proceedings of the 54th Annual Design Automation Conference 2017, 1-6, 2017 | 5 | 2017 |
| Systolic-array spiking neural accelerators with dynamic heterogeneous voltage regulation JJ Lee, J Chen, W Zhang, P Li 2021 International Joint Conference on Neural Networks (IJCNN), 1-7, 2021 | 4 | 2021 |
| SaARSP: An Architecture for Systolic-Array Acceleration of Recurrent Spiking Neural Networks JJ Lee, W Zhang, Y Xie, P Li ACM Journal on Emerging Technologies in Computing Systems (JETC) 18 (4), 1-23, 2022 | 2 | 2022 |
| Efficient Biologically-Plausible Training of Spiking Neural Networks with Precise Timing R Boone, W Zhang, P Li International Conference on Neuromorphic Systems 2021, 1-8, 2021 | 1 | 2021 |
| Improved Stereo Matching based on Convolutional Neural Network Y Geng, M Lu, B Ding, W Zhang, Y Hua Proceedings of the International Conference on Image Processing, Computer …, 2019 | | 2019 |
Peng LiProfessor of Electrical & Computer Engineering, University of California, Santa BarbaraVerified email at ucsb.edu
