Zobrazeno 1 - 10
of 184
pro vyhledávání: '"Peng, Huimin"'
Autor:
Zhong, Jinrui, Duan, Junxi, Zhang, Shihao, Peng, Huimin, Feng, Qi, Hu, Yuqin, Wang, Qinsheng, Mao, Jinhai, Liu, Jianpeng, Yao, Yugui
The second-order nonlinear Hall effect illuminates a frequency-doubling transverse current emerging in quantum materials with broken inversion symmetry even when time-reversal symmetry is preserved. This nonlinear response originates from both the Be
Externí odkaz:
http://arxiv.org/abs/2301.12117
In the second-order response regime, the Hall voltage can be nonzero without breaking the time-reversal symmetry, as long as the system is noncentrosymmetric. There are multiple mechanisms with different scaling rules that contribute to the nonlinear
Externí odkaz:
http://arxiv.org/abs/2201.09274
Autor:
Peng, Huimin1 (AUTHOR), Zhong, Jinrui1 (AUTHOR), Feng, Qi1 (AUTHOR), Hu, Yuqing1 (AUTHOR), Li, Qiuli1 (AUTHOR), Zhang, Shihao2 (AUTHOR) zhangshh@hnu.edu.cn, Mao, Jinhai3 (AUTHOR) jhmao@ucas.ac.cn, Duan, Junxi1 (AUTHOR) junxi.duan@bit.edu.cn, Yao, Yugui1 (AUTHOR)
Publikováno v:
Communications Physics. 7/15/2024, Vol. 7 Issue 1, p1-7. 7p.
Autor:
Peng, Huimin1 (AUTHOR), Jing, Longjun1 (AUTHOR), Liu, Yang2 (AUTHOR), Tang, Yiwei1 (AUTHOR), Wang, Huilin3 (AUTHOR)
Publikováno v:
Social Behavior & Personality: an international journal. Jun2024, Vol. 52 Issue 6, p1-10. 10p.
Autor:
Chen, Yanbing, Peng, Huimin, Zhuang, Kai, Xie, Wenting, Li, Chenli, Chen, Meiqin, Xue, Jin, Huang, Xiaoting, Zou, Tingting, Sun, Hao, Lei, Aiyu, Wang, Ya, Can, Dan, Li, Huifang, Yuan, Tifei, Zhang, Jie
Publikováno v:
In iScience 17 May 2024 27(5)
Autor:
Peng, Huimin
General AI system solves a wide range of tasks with high performance in an automated fashion. The best general AI algorithm designed by one individual is different from that devised by another. The best performance records achieved by different users
Externí odkaz:
http://arxiv.org/abs/2103.14561
Autor:
Peng, Huimin
This paper briefly reviews the connections between meta-learning and self-supervised learning. Meta-learning can be applied to improve model generalization capability and to construct general AI algorithms. Self-supervised learning utilizes self-supe
Externí odkaz:
http://arxiv.org/abs/2103.00845
Autor:
Peng, Huimin
This paper briefly reviews the history of meta-learning and describes its contribution to general AI. Meta-learning improves model generalization capacity and devises general algorithms applicable to both in-distribution and out-of-distribution tasks
Externí odkaz:
http://arxiv.org/abs/2101.04283
Autor:
Peng, Huimin
This article reviews meta-learning also known as learning-to-learn which seeks rapid and accurate model adaptation to unseen tasks with applications in highly automated AI, few-shot learning, natural language processing and robotics. Unlike deep lear
Externí odkaz:
http://arxiv.org/abs/2004.11149
Autor:
Peng, Huimin
This article reviews bias-correction models for measurement error of exposure variables in the field of nutritional epidemiology. Measurement error usually attenuates estimated slope towards zero. Due to the influence of measurement error, inference
Externí odkaz:
http://arxiv.org/abs/2004.06448