1.9k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN353 papers
- University of Chinese Academy of SciencesCN228 papers
- Shandong Institute of AutomationCN78 papers
- Beijing Academy of Artificial IntelligenceCN58 papers
- Center for Excellence in Brain Science and Intelligence TechnologyCN57 papers
- Tsinghua UniversityCN26 papers
- Peking UniversityCN16 papers
- National University of SingaporeSG13 papers
- Beijing University of Posts and TelecommunicationsCN12 papers
- Beihang UniversityCN11 papers
- University of Science and Technology of ChinaCN11 papers
- Anhui UniversityCN9 papers
14 papers · 1 filter
Towards Efficient and Accurate Spiking Neural Networks via Adaptive Bit Allocation
Xingting Yao, Qinghao Hu, Fei Zhou +4
Multi-bit spiking neural networks (SNNs) have recently become a heated research spot, pursuing energy-efficient and high-accurate AI. However, with more bits involved, the associat…
Speck: A Smart event-based Vision Sensor with a low latency 327K Neuron Convolutional Neuronal Network Processing Pipeline
Ole Richter, Yannan Xing, Michele De Marchi +9
Edge computing solutions that enable the extraction of high-level information from a variety of sensors is in increasingly high demand. This is due to the increasing number of smar…
Tuning Synaptic Connections instead of Weights by Genetic Algorithm in Spiking Policy Network
Duzhen Zhang, Tielin Zhang, Shuncheng Jia +2
Learning from interaction is the primary way that biological agents acquire knowledge about their environment and themselves. Modern deep reinforcement learning (DRL) explores a co…
FireFly: A High-Throughput Hardware Accelerator for Spiking Neural Networks with Efficient DSP and Memory Optimization
Jindong Li, Guobin Shen, Dongcheng Zhao +2
Spiking neural networks (SNNs) have been widely used due to their strong biological interpretability and high energy efficiency. With the introduction of the backpropagation algori…
BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation
Yi Zeng, Dongcheng Zhao, Feifei Zhao +16
Spiking neural networks (SNNs) have attracted extensive attentions in Brain-inspired Artificial Intelligence and computational neuroscience. They can be used to simulate biological…
Pareto Optimization or Cascaded Weighted Sum: A Comparison of Concepts
Wilfried Jakob, Christian Blume
According to the published papers and books since the turn of the century, Pareto optimization is the dominating assessment method for multi-objective nonlinear optimization proble…
Towards Best Practice of Interpreting Deep Learning Models for EEG-based Brain Computer Interfaces
Jian Cui, Liqiang Yuan, Zhaoxiang Wang +2
As deep learning has achieved state-of-the-art performance for many tasks of EEG-based BCI, many efforts have been made in recent years trying to understand what have been learned…
N-Omniglot, a large-scale neuromorphic dataset for spatio-temporal sparse few-shot learning
Yang Li, Yiting Dong, Dongcheng Zhao +1
Few-shot learning (learning with a few samples) is one of the most important cognitive abilities of the human brain. However, the current artificial intelligence systems meet diffi…
Quantum Superposition Inspired Spiking Neural Network
Yinqian Sun, Yi Zeng, Tielin Zhang
Despite advances in artificial intelligence models, neural networks still cannot achieve human performance, partly due to differences in how information is encoded and processed co…
Angle-based Search Space Shrinking for Neural Architecture Search
Yiming Hu, Yuding Liang, Zichao Guo +5
In this work, we present a simple and general search space shrinking method, called Angle-Based search space Shrinking (ABS), for Neural Architecture Search (NAS). Our approach pro…
A Biologically Plausible Supervised Learning Method for Spiking Neural Networks Using the Symmetric STDP Rule
Yunzhe Hao, Xuhui Huang, Meng Dong +1
Spiking neural networks (SNNs) possess energy-efficient potential due to event-based computation. However, supervised training of SNNs remains a challenge as spike activities are n…
Reinforced Evolutionary Neural Architecture Search
Yukang Chen, Gaofeng Meng, Qian Zhang +4
Neural Architecture Search (NAS) is an important yet challenging task in network design due to its high computational consumption. To address this issue, we propose the Reinforced…
Transfer Learning based Dynamic Multiobjective Optimization Algorithms
Min Jiang, Zhongqiang Huang, Liming Qiu +2
One of the major distinguishing features of the dynamic multiobjective optimization problems (DMOPs) is the optimization objectives will change over time, thus tracking the varying…
Locally Imposing Function for Generalized Constraint Neural Networks - A Study on Equality Constraints
Linlin Cao, Ran He, Bao-Gang Hu
This work is a further study on the Generalized Constraint Neural Network (GCNN) model [1], [2]. Two challenges are encountered in the study, that is, to embed any type of prior in…