| Temporal efficient training of spiking neural network via gradient re-weighting S Deng, Y Li, S Zhang, S Gu arXiv preprint arXiv:2202.11946, 2022 | 285 | 2022 |
| Differentiable spike: Rethinking gradient-descent for training spiking neural networks Y Li, Y Guo, S Zhang, S Deng, Y Hai, S Gu Advances in Neural Information Processing Systems 34, 23426-23439, 2021 | 261 | 2021 |
| Optimal conversion of conventional artificial neural networks to spiking neural networks S Deng, S Gu arXiv preprint arXiv:2103.00476, 2021 | 241 | 2021 |
| A free lunch from ANN: Towards efficient, accurate spiking neural networks calibration Y Li, S Deng, X Dong, R Gong, S Gu International conference on machine learning, 6316-6325, 2021 | 215 | 2021 |
| Controllability of functional brain networks and its clinical significance in first-episode schizophrenia Q Li, L Yao, W You, J Liu, S Deng, B Li, L Luo, Y Zhao, Y Wang, Y Wang, ... Schizophrenia Bulletin 49 (3), 659-668, 2023 | 39 | 2023 |
| Converting artificial neural networks to spiking neural networks via parameter calibration Y Li, S Deng, X Dong, S Gu arXiv preprint arXiv:2205.10121, 2022 | 28 | 2022 |
| Control theory illustrates the energy efficiency in the dynamic reconfiguration of functional connectivity S Deng, J Li, BT Thomas Yeo, S Gu Communications biology 5 (1), 295, 2022 | 18 | 2022 |
| Controllability analysis of functional brain networks S Deng, S Gu arXiv preprint arXiv:2003.08278, 2020 | 16 | 2020 |
| Surrogate module learning: Reduce the gradient error accumulation in training spiking neural networks S Deng, H Lin, Y Li, S Gu International Conference on Machine Learning, 7645-7657, 2023 | 15 | 2023 |
| Age-associated network controllability changes in first episode drug-naïve schizophrenia B Tang, W Zhang, S Deng, J Liu, N Hu, Q Gong, S Gu, S Lui BMC psychiatry 22, 1-9, 2022 | 8 | 2022 |
| Altered controllability of white matter networks and related brain function changes in first-episode drug-naive schizophrenia B Tang, W Zhang, J Liu, S Deng, N Hu, S Li, Y Zhao, N Liu, J Zeng, H Cao, ... Cerebral Cortex 33 (4), 1527-1535, 2023 | 5 | 2023 |
| Error-Aware Conversion from ANN to SNN via Post-training Parameter Calibration Y Li, S Deng, X Dong, S Gu International Journal of Computer Vision, 1-24, 2024 | 1 | 2024 |
| Transdiagnostic white matter controllability deficits across patients with affective and anxiety spectrum disorders B Tang, H Cao, S Deng, W Zhang, Y Zhao, Q Gong, S Gu, S Lui Journal of Affective Disorders 370, 268-276, 2025 | | 2025 |
| Controllability analysis on functional brain networks S Gu, S Deng arXiv preprint arXiv:2003.08278, 2019 | | 2019 |
| Spiking Token Mixer: An event-driven friendly Former structure for spiking neural networks S Deng, Y Wu, K Du, S Gu The Thirty-eighth Annual Conference on Neural Information Processing Systems, 0 | | |
| Temporal Flexibility in Spiking Neural Networks: A Novel Training Method for Enhanced Generalization Across Time Steps K Du, Y Wu, S Deng, S Gu | | |
| Proper Backward Connection Placement Boosts Spiking Neural Networks S Deng, W Li, Y Wu, P Zheng, S Gu | | |
| Efficient Surrogate Gradients for Training Spiking Neural Networks H Lin, S Deng, S Gu | | |
| Synergistic Neuromorphic Federated Learning with ANN-SNN Conversion For Privacy Protection Y Chen, S Deng, Y Li, X Dong, S Gu Available at SSRN 4453238, 0 | | |
Shi GuUniversity of Electronic Science and Technology of ChinaVerified email at sas.upenn.edu