Yang Li
Affiliations:- Chinese Academy of Sciences, Institute of Automation, Research Center for Brain-Inspired Intelligence, Beijing, China
- University of Chinese Academy of Sciences, School of Artificial Intelligence, Beijing, China
According to our database1,
Yang Li
authored at least 15 papers
between 2021 and 2024.
Collaborative distances:
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Timeline
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Bibliography
2024
MSAT: biologically inspired multistage adaptive threshold for conversion of spiking neural networks.
Neural Comput. Appl., May, 2024
2023
BrainCog: A spiking neural network based, brain-inspired cognitive intelligence engine for brain-inspired AI and brain simulation.
Patterns, August, 2023
An unsupervised STDP-based spiking neural network inspired by biologically plausible learning rules and connections.
Neural Networks, August, 2023
Metaplasticity: Unifying Learning and Homeostatic Plasticity in Spiking Neural Networks.
CoRR, 2023
Improving Stability and Performance of Spiking Neural Networks through Enhancing Temporal Consistency.
CoRR, 2023
Improving the Performance of Spiking Neural Networks on Event-based Datasets with Knowledge Transfer.
CoRR, 2023
2022
BackEISNN: A deep spiking neural network with adaptive self-feedback and balanced excitatory-inhibitory neurons.
Neural Networks, 2022
Spiking CapsNet: A spiking neural network with a biologically plausible routing rule between capsules.
Inf. Sci., 2022
An Unsupervised Spiking Neural Network Inspired By Biologically Plausible Learning Rules and Connections.
CoRR, 2022
Spike Calibration: Fast and Accurate Conversion of Spiking Neural Network for Object Detection and Segmentation.
CoRR, 2022
Solving the Spike Feature Information Vanishing Problem in Spiking Deep Q Network with Potential Based Normalization.
CoRR, 2022
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
2021
N-Omniglot: a Large-scale Neuromorphic Dataset for Spatio-Temporal Sparse Few-shot Learning.
CoRR, 2021
BSNN: Towards Faster and Better Conversion of Artificial Neural Networks to Spiking Neural Networks with Bistable Neurons.
CoRR, 2021