88 citations
- Tsinghua UniversityCN12 papers
- Beijing Academy of Artificial IntelligenceCN5 papers
- Beijing Normal UniversityCN5 papers
- McGovern Institute for Brain ResearchUS5 papers
- Peking UniversityCN5 papers
- Center for Life SciencesCN4 papers
- Chinese Academy of SciencesCN3 papers
- Beihang UniversityCN2 papers
- Beijing Forestry UniversityCN2 papers
- Chinese Academy of Medical Sciences & Peking Union Medical CollegeCN2 papers
- Swansea UniversityGB2 papers
- University of Chinese Academy of SciencesCN2 papers
5 papers · 1 filter
Incorporating Neuro-Inspired Adaptability for Continual Learning in Artificial Intelligence
Liyuan Wang, Xingxing Zhang, Qian Li +4
Continual learning aims to empower artificial intelligence (AI) with strong adaptability to the real world. For this purpose, a desirable solution should properly balance memory st…
Probabilistic Compute-in-Memory Design For Efficient Markov Chain Monte Carlo Sampling
Yihan Fu, Daijing Shi, Anjunyi Fan +4
Markov chain Monte Carlo (MCMC) is a widely used sampling method in modern artificial intelligence and probabilistic computing systems. It involves repetitive random number generat…
Amplification trojan network: Attack deep neural networks by amplifying their inherent weakness
Zhanhao Hu, Jun Zhu, Bo Zhang +1
Recent works found that deep neural networks (DNNs) can be fooled by adversarial examples, which are crafted by adding adversarial noise on clean inputs. The accuracy of DNNs on ad…
LiNbO volatile memristors for reservoir computing
Zhao Yuanxi, Duan Wenrui, Li Huanglong
In conventional digital computers, data and information are represented in binary form and encoded in the steady states of transistors. They are then processed in a quasi-static wa…
Moment-based space-variant Shack-Hartmann wavefront reconstruction
Fan Feng, Chen Liang, Dongdong Chen +9
Based on image moment theory, an approach for space-variant Shack-Hartmann wavefront reconstruction is presented in this article. The relation between the moment of a pair of subim…