Zobrazeno 1 - 10
of 4 010
pro vyhledávání: '"Xiaozhu A"'
Autor:
Wu, Kun, Hou, Chengkai, Liu, Jiaming, Che, Zhengping, Ju, Xiaozhu, Yang, Zhuqin, Li, Meng, Zhao, Yinuo, Xu, Zhiyuan, Yang, Guang, Zhao, Zhen, Li, Guangyu, Jin, Zhao, Wang, Lecheng, Mao, Jilei, Wang, Xinhua, Fan, Shichao, Liu, Ning, Ren, Pei, Zhang, Qiang, Lyu, Yaoxu, Liu, Mengzhen, He, Jingyang, Luo, Yulin, Gao, Zeyu, Li, Chenxuan, Gu, Chenyang, Fu, Yankai, Wu, Di, Wang, Xingyu, Chen, Sixiang, Wang, Zhenyu, An, Pengju, Qian, Siyuan, Zhang, Shanghang, Tang, Jian
Developing robust and general-purpose robotic manipulation policies is a key goal in the field of robotics. To achieve effective generalization, it is essential to construct comprehensive datasets that encompass a large number of demonstration trajec
Externí odkaz:
http://arxiv.org/abs/2412.13877
Speech foundation models, exemplified by OpenAI's Whisper, have emerged as leaders in speech understanding thanks to their exceptional accuracy and adaptability. However, their usage largely focuses on processing pre-recorded audio, with the efficien
Externí odkaz:
http://arxiv.org/abs/2412.11272
To deploy LLMs on resource-contained platforms such as mobile robotics and wearables, non-transformers LLMs have achieved major breakthroughs. Recently, a novel RNN-based LLM family, Repentance Weighted Key Value (RWKV) models have shown promising re
Externí odkaz:
http://arxiv.org/abs/2412.10856
Autor:
Ma, Haoyu, Chen, Yushu, Zhao, Wenlai, Yang, Jinzhe, Ji, Yingsheng, Xu, Xinghua, Liu, Xiaozhu, Jing, Hao, Liu, Shengzhuo, Yang, Guangwen
Time series foundation models have demonstrated strong performance in zero-shot learning, making them well-suited for predicting rapidly evolving patterns in real-world applications where relevant training data are scarce. However, most of these mode
Externí odkaz:
http://arxiv.org/abs/2411.02941
Enzymes are biological catalysts that can accelerate chemical reactions compared to uncatalyzed reactions in aqueous environments. Their catalytic efficiency is quantified by the turnover number (kcat), a parameter in enzyme kinetics. Enhancing enzym
Externí odkaz:
http://arxiv.org/abs/2411.01745
The pursuit of agile and efficient underwater robots, especially bio-mimetic robotic fish, has been impeded by challenges in creating motion controllers that are able to fully exploit their hydrodynamic capabilities. This paper addresses these challe
Externí odkaz:
http://arxiv.org/abs/2409.10019
The identification of continuous-time (CT) systems from discrete-time (DT) input and output signals, i.e., the sampled data, has received considerable attention for half a century. The state-of-the-art methods are parametric methods and thus subject
Externí odkaz:
http://arxiv.org/abs/2409.09299
Frequency response function (FRF) estimation is a classical subject in system identification. In the past two decades, there have been remarkable advances in developing local methods for this subject, e.g., the local polynomial method, local rational
Externí odkaz:
http://arxiv.org/abs/2405.12629
Publikováno v:
Physical Review Letters 125.21 (2020): 218301
Spreading phenomena essentially underlie the dynamics of various natural and technological networked systems, yet how spatiotemporal propagation patterns emerge from such networks remains largely unknown. Here we propose a novel approach that reveals
Externí odkaz:
http://arxiv.org/abs/2403.05797
Autor:
Zhang, Xiaozhu, Timme, Marc
Publikováno v:
European Journal of Applied Mathematics (2022) 1-38
Networked dynamical systems, i.e., systems of dynamical units coupled via nontrivial interaction topologies, constitute models of broad classes of complex systems, ranging from gene regulatory and metabolic circuits in our cells to pandemics spreadin
Externí odkaz:
http://arxiv.org/abs/2403.05746