Zobrazeno 1 - 10
of 930
pro vyhledávání: '"Li Guoqi"'
Publikováno v:
Redai dili, Vol 42, Iss 11, Pp 1806-1815 (2022)
Against the background of the increasing trend of fragmentation of freight demand, the spatial structure analysis of urban networks using road Less-Truck-Load (LTL) dedicated lines has positive implications for enriching the flow space theory and emp
Externí odkaz:
https://doaj.org/article/5c44539d30d84a409eb34c0426878172
The Forward-Forward (FF) algorithm was recently proposed as a local learning method to address the limitations of backpropagation (BP), offering biological plausibility along with memory-efficient and highly parallelized computational benefits. Howev
Externí odkaz:
http://arxiv.org/abs/2408.14925
We introduce AiM, an autoregressive (AR) image generative model based on Mamba architecture. AiM employs Mamba, a novel state-space model characterized by its exceptional performance for long-sequence modeling with linear time complexity, to supplant
Externí odkaz:
http://arxiv.org/abs/2408.12245
Deep learning has revolutionized artificial intelligence (AI), achieving remarkable progress in fields such as computer vision, speech recognition, and natural language processing. Moreover, the recent success of large language models (LLMs) has fuel
Externí odkaz:
http://arxiv.org/abs/2409.02111
Brain-inspired Spiking Neural Networks (SNNs) have bio-plausibility and low-power advantages over Artificial Neural Networks (ANNs). Applications of SNNs are currently limited to simple classification tasks because of their poor performance. In this
Externí odkaz:
http://arxiv.org/abs/2407.20708
Autor:
Xu, Mingkun, Yin, Huifeng, Wu, Yujie, Li, Guoqi, Liu, Faqiang, Pei, Jing, Zhong, Shuai, Deng, Lei
In recent years, spiking neural networks (SNNs) have attracted substantial interest due to their potential to replicate the energy-efficient and event-driven processing of biological neurons. Despite this, the application of SNNs in graph representat
Externí odkaz:
http://arxiv.org/abs/2407.20508
Spiking Neural Networks (SNNs) have received widespread attention due to their unique neuronal dynamics and low-power nature. Previous research empirically shows that SNNs with Poisson coding are more robust than Artificial Neural Networks (ANNs) on
Externí odkaz:
http://arxiv.org/abs/2407.20099
Autor:
Wang, Bo, Wang, Shaocong, Lin, Ning, Li, Yi, Yu, Yifei, Zhang, Yue, Yang, Jichang, Wu, Xiaoshan, He, Yangu, Wang, Songqi, Chen, Rui, Li, Guoqi, Qi, Xiaojuan, Wang, Zhongrui, Shang, Dashan
There is unprecedented development in machine learning, exemplified by recent large language models and world simulators, which are artificial neural networks running on digital computers. However, they still cannot parallel human brains in terms of
Externí odkaz:
http://arxiv.org/abs/2407.18625
Brain-inspired Spiking Neural Network (SNN) has demonstrated its effectiveness and efficiency in vision, natural language, and speech understanding tasks, indicating their capacity to "see", "listen", and "read". In this paper, we design \textbf{Spik
Externí odkaz:
http://arxiv.org/abs/2408.00788
Autor:
Xing, Xingrun, Gao, Boyan, Zhang, Zheng, Clifton, David A., Xiao, Shitao, Du, Li, Li, Guoqi, Zhang, Jiajun
The recent advancements in large language models (LLMs) with billions of parameters have significantly boosted their performance across various real-world applications. However, the inference processes for these models require substantial energy and
Externí odkaz:
http://arxiv.org/abs/2407.04752