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Yuhang Li
Yuhang Li
在 yale.edu 的电子邮件经过验证
标题
引用次数
引用次数
年份
Additive powers-of-two quantization: An efficient non-uniform discretization for neural networks
Y Li, X Dong, W Wang
International Conference on Learning Representations 2020, 2019
2852019
Brecq: Pushing the limit of post-training quantization by block reconstruction
Y Li, R Gong, X Tan, Y Yang, P Hu, Q Zhang, F Yu, W Wang, S Gu
International Conference on Learning Representations 2021, 2021
2842021
Temporal Efficient Training of Spiking Neural Network via Gradient Re-weighting
S Deng, Y Li, S Zhang, S Gu
International Conference on Learning Representations, 2022
1902022
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
1802021
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
1602021
Diversifying sample generation for accurate data-free quantization
X Zhang, H Qin, Y Ding, R Gong, Q Yan, R Tao, Y Li, F Yu, X Liu
Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021
872021
Neural architecture search for spiking neural networks
Y Kim, Y Li, H Park, Y Venkatesha, P Panda
Proceedings of the 17th European Conference on Computer Vision (ECCV 2022), 2022
852022
Qdrop: Randomly dropping quantization for extremely low-bit post-training quantization
X Wei, R Gong, Y Li, X Liu, F Yu
arXiv preprint arXiv:2203.05740, 2022
792022
Neuromorphic Data Augmentation for Training Spiking Neural Networks
Y Li, Y Kim, H Park, T Geller, P Panda
Proceedings of the 17th European Conference on Computer Vision (ECCV 2022), 2022
672022
MQBench: Towards Reproducible and Deployable Model Quantization Benchmark
Y Li, M Shen, J Ma, Y Ren, M Zhao, Q Zhang, R Gong, F Yu, J Yan
Thirty-fifth Conference on Neural Information Processing Systems Datasets …, 2021
462021
Exploring Lottery Ticket Hypothesis in Spiking Neural Networks
Y Kim, Y Li, H Park, Y Venkatesha, R Yin, P Panda
arXiv preprint arXiv:2207.01382, 2022
412022
Outlier Suppression+: Accurate quantization of large language models by equivalent and optimal shifting and scaling
X Wei, Y Zhang, Y Li, X Zhang, R Gong, J Guo, X Liu
EMNLP 2023, 2023
392023
Mixmix: All you need for data-free compression are feature and data mixing
Y Li, F Zhu, R Gong, M Shen, X Dong, F Yu, S Lu, S Gu
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
342021
Once quantization-aware training: High performance extremely low-bit architecture search
M Shen, F Liang, R Gong, Y Li, C Li, C Lin, F Yu, J Yan, W Ouyang
Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021
30*2021
Rtn: Reparameterized ternary network
Y Li, X Dong, SQ Zhang, H Bai, Y Chen, W Wang
Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4780-4787, 2020
282020
Efficient bitwidth search for practical mixed precision neural network
Y Li, W Wang, H Bai, R Gong, X Dong, F Yu
arXiv preprint arXiv:2003.07577, 2020
182020
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
17*2024
Exploring Temporal Information Dynamics in Spiking Neural Networks
Y Kim, Y Li, H Park, Y Venkatesha, A Hambitzer, P Panda
AAAI 2023 (preprint arXiv:2211.14406), 2022
132022
SEENN: Towards Temporal Spiking Early-Exit Neural Networks
Y Li, T Geller, Y Kim, P Panda
NeurIPS 2023, 2023
122023
Data-driven spatio-temporal analysis via multi-modal zeitgebers and cognitive load in VR
H Liao, N Xie, H Li, Y Li, J Su, F Jiang, W Huang, HT Shen
2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR), 473-482, 2020
102020
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