Zobrazeno 1 - 10
of 689
pro vyhledávání: '"Li, Jindong"'
Systolic architectures are widely embraced by neural network accelerators for their superior performance in highly parallelized computation. The DSP48E2s serve as dedicated arithmetic blocks in Xilinx Ultrascale series FPGAs and constitute a fundamen
Externí odkaz:
http://arxiv.org/abs/2409.03508
Spiking Neural Networks (SNNs), with their brain-inspired structure using discrete spikes instead of continuous activations, are gaining attention for their potential of efficient processing on neuromorphic chips. While current SNN hardware accelerat
Externí odkaz:
http://arxiv.org/abs/2408.15578
Unsupervised graph-level anomaly detection (UGAD) has garnered increasing attention in recent years due to its significance. However, most existing methods only rely on traditional graph neural networks to explore pairwise relationships but such kind
Externí odkaz:
http://arxiv.org/abs/2407.02057
Unsupervised graph-level anomaly detection (UGAD) has attracted increasing interest due to its widespread application. In recent studies, knowledge distillation-based methods have been widely used in unsupervised anomaly detection to improve model ef
Externí odkaz:
http://arxiv.org/abs/2407.00383
Unsupervised graph-level anomaly detection (UGAD) has received remarkable performance in various critical disciplines, such as chemistry analysis and bioinformatics. Existing UGAD paradigms often adopt data augmentation techniques to construct multip
Externí odkaz:
http://arxiv.org/abs/2405.02359
Autor:
Niu, Runliang, Li, Jindong, Wang, Shiqi, Fu, Yali, Hu, Xiyu, Leng, Xueyuan, Kong, He, Chang, Yi, Wang, Qi
Existing Large Language Models (LLM) can invoke a variety of tools and APIs to complete complex tasks. The computer, as the most powerful and universal tool, could potentially be controlled directly by a trained LLM agent. Powered by the computer, we
Externí odkaz:
http://arxiv.org/abs/2402.07945
Within the complex neuroarchitecture of the brain, astrocytes play crucial roles in development, structure, and metabolism. These cells regulate neural activity through tripartite synapses, directly impacting cognitive processes such as learning and
Externí odkaz:
http://arxiv.org/abs/2312.07625
Point cloud registration (PCR) is an essential task in 3D vision. Existing methods achieve increasingly higher accuracy. However, a large proportion of non-overlapping points in point cloud registration consume a lot of computational resources while
Externí odkaz:
http://arxiv.org/abs/2312.02877
Spiking Neural Networks (SNNs) have been widely praised for their high energy efficiency and immense potential. However, comprehensive research that critically contrasts and correlates SNNs with quantized Artificial Neural Networks (ANNs) remains sca
Externí odkaz:
http://arxiv.org/abs/2311.10802
Spiking Neural Networks (SNNs) are expected to be a promising alternative to Artificial Neural Networks (ANNs) due to their strong biological interpretability and high energy efficiency. Specialized SNN hardware offers clear advantages over general-p
Externí odkaz:
http://arxiv.org/abs/2309.16158