Articles with public access mandates - Yuhang LiLearn more
Available somewhere: 19
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
Mandates: US National Science Foundation
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
Mandates: National Natural Science Foundation of China
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
Mandates: US National Science Foundation, US Department of Defense
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
Mandates: US National Science Foundation, US Department of Defense
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
Mandates: National Natural Science Foundation of China
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
Mandates: US National Science Foundation, US Department of Defense
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
Mandates: Australian Research Council, Medical Research Future Fund, Australia
SEENN: Towards Temporal Spiking Early-Exit Neural Networks
Y Li, T Geller, Y Kim, P Panda
NeurIPS 2023, 2023
Mandates: US National Science Foundation, US Department of Energy, US Department of …
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
Mandates: US National Science Foundation, US Department of Defense
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
Mandates: National Natural Science Foundation of China
Efficient human activity recognition with spatio-temporal spiking neural networks
Y Li, R Yin, Y Kim, P Panda
Frontiers in Neuroscience 17, 1233037, 2023
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Surrogate Module Learning: Reduce the Gradient Error Accumulation in Training Spiking Neural Networks
S Deng, H Lin, Y Li, S Gu
ICML 2023, 2023
Mandates: National Natural Science Foundation of China
Input-Aware Dynamic Timestep Spiking Neural Networks for Efficient In-Memory Computing
Y Li, A Moitra, T Geller, P Panda
Design and Automation Conference 2023, 2023
Mandates: US National Science Foundation, US Department of Energy, US Department of …
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
Mandates: National Natural Science Foundation of China
Sharing leaky-integrate-and-fire neurons for memory-efficient spiking neural networks
Y Kim, Y Li, A Moitra, R Yin, P Panda
Frontiers in Neuroscience 17, 1230002, 2023
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Addressing client drift in federated continual learning with adaptive optimization
Y Venkatesha, Y Kim, H Park, Y Li, P Panda
Available at SSRN 4188586, 2022
Mandates: US National Science Foundation, US Department of Defense
TT-SNN: tensor train decomposition for efficient spiking neural network training
D Lee, R Yin, Y Kim, A Moitra, Y Li, P Panda
2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-6, 2024
Mandates: US National Science Foundation, US Department of Energy, US Department of …
Rethinking skip connections in spiking neural networks with time-to-first-spike coding
Y Kim, A Kahana, R Yin, Y Li, P Stinis, GE Karniadakis, P Panda
Frontiers in Neuroscience 18, 1346805, 2024
Mandates: US National Science Foundation, US Department of Energy, US Department of …
SysNoise: Exploring and Benchmarking Training-Deployment System Inconsistency
Y Wang, Y Li, R Gong, A Liu, J Hu, Y Yao, Y Zhang, F Yu, X Liu
Proceedings of Machine Learning and Systems 5, 354-372, 2023
Mandates: National Natural Science Foundation of China
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