Zobrazeno 1 - 10
of 39 605
pro vyhledávání: '"LI, RUI"'
Autor:
Li, Rui
Recent advancements in inverse rendering have exhibited promising results for 3D representation, novel view synthesis, scene parameter reconstruction, and direct graphical asset generation and editing. Inverse rendering attempts to recover the scene
Externí odkaz:
http://hdl.handle.net/10754/693530
Datasets play a pivotal role in training visual models, facilitating the development of abstract understandings of visual features through diverse image samples and multidimensional attributes. However, in the realm of aesthetic evaluation of artisti
Externí odkaz:
http://arxiv.org/abs/2411.08545
This work explores the intersection of continual learning (CL) and differential privacy (DP). Crucially, continual learning models must retain knowledge across tasks, but this conflicts with the differential privacy requirement of restricting individ
Externí odkaz:
http://arxiv.org/abs/2411.04680
Helical Kelvin waves were conjectured to exist for the 3D Euler equations in Lucas and Dritschel \cite{LucDri} (as well as in \cite{Chu}) by studying dispersion relation for infinitesimal linear perturbations of a circular helically symmetric vortex
Externí odkaz:
http://arxiv.org/abs/2411.02055
Autor:
Wang, Fali, Zhang, Zhiwei, Zhang, Xianren, Wu, Zongyu, Mo, Tzuhao, Lu, Qiuhao, Wang, Wanjing, Li, Rui, Xu, Junjie, Tang, Xianfeng, He, Qi, Ma, Yao, Huang, Ming, Wang, Suhang
Large language models (LLM) have demonstrated emergent abilities in text generation, question answering, and reasoning, facilitating various tasks and domains. Despite their proficiency in various tasks, LLMs like LaPM 540B and Llama-3.1 405B face li
Externí odkaz:
http://arxiv.org/abs/2411.03350
Autor:
Lin, Qiufan, Ruan, Hengxin, Fouchez, Dominique, Chen, Shupei, Li, Rui, Montero-Camacho, Paulo, Napolitano, Nicola R., Ting, Yuan-Sen, Zhang, Wei
Obtaining well-calibrated photometric redshift probability densities for galaxies without a spectroscopic measurement remains a challenge. Deep learning discriminative models, typically fed with multi-band galaxy images, can produce outputs that mimi
Externí odkaz:
http://arxiv.org/abs/2410.19390
Neural networks (NNs) have been widely used to solve partial differential equations (PDEs) in the applications of physics, biology, and engineering. One effective approach for solving PDEs with a fixed differential operator is learning Green's functi
Externí odkaz:
http://arxiv.org/abs/2410.18439
Autor:
Hou, Shuyang, Shen, Zhangxiao, Zhao, Anqi, Liang, Jianyuan, Gui, Zhipeng, Guan, Xuefeng, Li, Rui, Wu, Huayi
The increasing demand for spatiotemporal data and modeling tasks in geosciences has made geospatial code generation technology a critical factor in enhancing productivity. Although large language models (LLMs) have demonstrated potential in code gene
Externí odkaz:
http://arxiv.org/abs/2410.17031
With the growing demand for spatiotemporal data processing and geospatial modeling, automating geospatial code generation has become essential for productivity. Large language models (LLMs) show promise in code generation but face challenges like dom
Externí odkaz:
http://arxiv.org/abs/2410.09738
Autor:
Wang, Qi, Li, Jindong, Wang, Shiqi, Xing, Qianli, Niu, Runliang, Kong, He, Li, Rui, Long, Guodong, Chang, Yi, Zhang, Chengqi
Large language models (LLMs) have not only revolutionized the field of natural language processing (NLP) but also have the potential to bring a paradigm shift in many other fields due to their remarkable abilities of language understanding, as well a
Externí odkaz:
http://arxiv.org/abs/2410.19744