no code implementations • 30 Apr 2024 • Guobin Shen, Dongcheng Zhao, Xiang He, Linghao Feng, Yiting Dong, Jihang Wang, Qian Zhang, Yi Zeng
This extractor consolidates multi-level visual features into one network, simplifying integration with Large Language Models (LLMs).
no code implementations • 29 Feb 2024 • Yi Zeng, Feifei Zhao, Yuxuan Zhao, Dongcheng Zhao, Enmeng Lu, Qian Zhang, Yuwei Wang, Hui Feng, Zhuoya Zhao, Jihang Wang, Qingqun Kong, Yinqian Sun, Yang Li, Guobin Shen, Bing Han, Yiting Dong, Wenxuan Pan, Xiang He, Aorigele Bao, Jin Wang
In this paper, we introduce a Brain-inspired and Self-based Artificial Intelligence (BriSe AI) paradigm.
no code implementations • 1 Feb 2024 • Yang Li, Yinqian Sun, Xiang He, Yiting Dong, Dongcheng Zhao, Yi Zeng
Efficient parallel computing has become a pivotal element in advancing artificial intelligence.
no code implementations • 12 Dec 2023 • Guobin Shen, Dongcheng Zhao, Yiting Dong, Yang Li, Jindong Li, Kang Sun, Yi Zeng
Within the complex neuroarchitecture of the brain, astrocytes play crucial roles in development, structure, and metabolism.
no code implementations • 23 Aug 2023 • Guobin Shen, Dongcheng Zhao, Yiting Dong, Yang Li, Feifei Zhao, Yi Zeng
This shift in focus from weight adjustment to mastering the intricacies of synaptic change offers a more flexible and dynamic pathway for neural networks to evolve and adapt.
no code implementations • 23 May 2023 • Dongcheng Zhao, Guobin Shen, Yiting Dong, Yang Li, Yi Zeng
Notably, our algorithm has achieved state-of-the-art performance on neuromorphic datasets DVS-CIFAR10 and N-Caltech101, and can achieve superior performance in the test phase with timestep T=1.
no code implementations • 19 May 2023 • Guobin Shen, Dongcheng Zhao, Yiting Dong, Yang Li, Yi Zeng
The biological neural network is a vast and diverse structure with high neural heterogeneity.
no code implementations • 13 Apr 2023 • Yiting Dong, Dongcheng Zhao, Yi Zeng
However, SNNs typically grapple with challenges such as extended time steps, low temporal information utilization, and the requirement for consistent time step between testing and training.
no code implementations • 18 Jul 2022 • Yi Zeng, Dongcheng Zhao, Feifei Zhao, Guobin Shen, Yiting Dong, Enmeng Lu, Qian Zhang, Yinqian Sun, Qian Liang, Yuxuan Zhao, Zhuoya Zhao, Hongjian Fang, Yuwei Wang, Yang Li, Xin Liu, Chengcheng Du, Qingqun Kong, Zizhe Ruan, Weida Bi
These brain-inspired AI models have been effectively validated on various supervised, unsupervised, and reinforcement learning tasks, and they can be used to enable AI models to be with multiple brain-inspired cognitive functions.
no code implementations • 6 Jul 2022 • Yang Li, Xiang He, Yiting Dong, Qingqun Kong, Yi Zeng
Spiking neural network (SNN) has been attached to great importance due to the properties of high biological plausibility and low energy consumption on neuromorphic hardware.
no code implementations • 6 Jul 2022 • Yiting Dong, Dongcheng Zhao, Yang Li, Yi Zeng
By integrating the above three adaptive mechanisms and STB-STDP, our model greatly accelerates the training of unsupervised spiking neural networks and improves the performance of unsupervised SNNs on complex tasks.
1 code implementation • 25 Dec 2021 • Yang Li, Yiting Dong, Dongcheng Zhao, Yi Zeng
Few-shot learning (learning with a few samples) is one of the most important cognitive abilities of the human brain.