Zobrazeno 1 - 10
of 2 286
pro vyhledávání: '"Tao JIAN"'
Monte Carlo (MC) simulations, particularly using FLUKA, are essential for replicating real-world scenarios across scientific and engineering fields. Despite the robustness and versatility, FLUKA faces significant limitations in automation and integra
Externí odkaz:
http://arxiv.org/abs/2410.15222
Publikováno v:
Dynamic Data Driven Applications Systems 2024 (DDDAS2024)
The study focuses on developing a digital twin testbed tailored for public safety technologies, incorporating simulated wireless communication within the digital world. The integration enables rapid analysis of signal strength, facilitating effective
Externí odkaz:
http://arxiv.org/abs/2410.14140
This study presents a novel mechanical metallic reflector array to guide wireless signals to the point of interest, thereby enhancing received signal quality. Comprised of numerous individual units, this device, which acts as a linear Fresnel reflect
Externí odkaz:
http://arxiv.org/abs/2407.19179
Autor:
Liu, Zeyuan, Huan, Ziyu, Wang, Xiyao, Lyu, Jiafei, Tao, Jian, Li, Xiu, Huang, Furong, Xu, Huazhe
Reinforcement learning struggles in the face of long-horizon tasks and sparse goals due to the difficulty in manual reward specification. While existing methods address this by adding intrinsic rewards, they may fail to provide meaningful guidance in
Externí odkaz:
http://arxiv.org/abs/2406.07381
Exploration remains a critical issue in deep reinforcement learning for an agent to attain high returns in unknown environments. Although the prevailing exploration Random Network Distillation (RND) algorithm has been demonstrated to be effective in
Externí odkaz:
http://arxiv.org/abs/2401.09750
Autor:
Yang, Kai, Tao, Jian, Lyu, Jiafei, Ge, Chunjiang, Chen, Jiaxin, Li, Qimai, Shen, Weihan, Zhu, Xiaolong, Li, Xiu
Using reinforcement learning with human feedback (RLHF) has shown significant promise in fine-tuning diffusion models. Previous methods start by training a reward model that aligns with human preferences, then leverage RL techniques to fine-tune the
Externí odkaz:
http://arxiv.org/abs/2311.13231
Autor:
Yu Pan, Tao Jian, Pingfan Gu, Yiwen Song, Qi Wang, Bo Han, Yuqia Ran, Zemin Pan, Yanping Li, Wanjin Xu, Peng Gao, Chendong Zhang, Jun He, Xiaolong Xu, Yu Ye
Publikováno v:
Nature Communications, Vol 15, Iss 1, Pp 1-8 (2024)
Abstract The controllable fabrication of patterned p-type and n-type channels with precise doping control presents a significant challenge, impeding the realization of complementary metal-oxide-semiconductor (CMOS) logic using a single van der Waals
Externí odkaz:
https://doaj.org/article/9fc800c888dd43dfb8815b02fddf7d29
Publikováno v:
Leida xuebao, Vol 13, Iss 5, Pp 1049-1060 (2024)
In multichannel adaptive radar target detection, diverse nonhomogeneous background factors can cause considerable outlier interference, making it challenging to meet the requirements of independent and identically distributed training data. Current m
Externí odkaz:
https://doaj.org/article/d4a0222689d640f4a56f73f6eed2582e
Publikováno v:
Computing&AI Connect, ISSN: 3006-4163; 2024, Vol. 1, Article ID: 2024001
Lossy compression has become an important technique to reduce data size in many domains. This type of compression is especially valuable for large-scale scientific data, whose size ranges up to several petabytes. Although Autoencoder-based models hav
Externí odkaz:
http://arxiv.org/abs/2307.04216