Zobrazeno 1 - 10
of 575
pro vyhledávání: '"LI Zehui"'
Autor:
Li Zehui
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Based on the KANO model, this paper identifies 27 basic demand items of digital rural services under service design thinking and constructs a rural digital service quality evaluation index system. At the same time, to determine the size of the impact
Externí odkaz:
https://doaj.org/article/46b6a7c953d64708a47fad7f5c0da170
Autor:
Li, Zehui, Ni, Yuhao, Xia, Guoxuan, Beardall, William, Das, Akashaditya, Stan, Guy-Bart, Zhao, Yiren
Abstract Recent advances in immunology and synthetic biology have accelerated the development of deep generative methods for DNA sequence design. Two dominant approaches in this field are AutoRegressive (AR) models and Diffusion Models (DMs). However
Externí odkaz:
http://arxiv.org/abs/2410.21345
Genetic variants (GVs) are defined as differences in the DNA sequences among individuals and play a crucial role in diagnosing and treating genetic diseases. The rapid decrease in next generation sequencing cost has led to an exponential increase in
Externí odkaz:
http://arxiv.org/abs/2407.16940
Autor:
Anwar, Nadia, Jiang, Guangya, Wen, Yi, Ahmed, Muqarrab, Zhong, Haodong, Ao, Shen, Li, Zehui, Ling, Yunhan, Schneider, Grégory F., Fu, Wangyang, Zhang, Zhengjun
In this review, the current advancements in electrochromic sensors based on two-dimensional (2D) materials with rich chemical and physical properties are critically examined. By summarizing the current trends in and prospects for utilizing multifunct
Externí odkaz:
http://arxiv.org/abs/2405.12352
Graph augmentation methods play a crucial role in improving the performance and enhancing generalisation capabilities in Graph Neural Networks (GNNs). Existing graph augmentation methods mainly perturb the graph structures, and are usually limited to
Externí odkaz:
http://arxiv.org/abs/2402.13033
Autor:
Li, Zehui, Ni, Yuhao, Beardall, William A V, Xia, Guoxuan, Das, Akashaditya, Stan, Guy-Bart, Zhao, Yiren
This paper introduces a novel framework for DNA sequence generation, comprising two key components: DiscDiff, a Latent Diffusion Model (LDM) tailored for generating discrete DNA sequences, and Absorb-Escape, a post-training algorithm designed to refi
Externí odkaz:
http://arxiv.org/abs/2402.06079
Autor:
Li, Zehui, Ni, Yuhao, Huygelen, Tim August B., Das, Akashaditya, Xia, Guoxuan, Stan, Guy-Bart, Zhao, Yiren
The harnessing of machine learning, especially deep generative models, has opened up promising avenues in the field of synthetic DNA sequence generation. Whilst Generative Adversarial Networks (GANs) have gained traction for this application, they of
Externí odkaz:
http://arxiv.org/abs/2310.06150
Given the increasing volume and quality of genomics data, extracting new insights requires interpretable machine-learning models. This work presents Genomic Interpreter: a novel architecture for genomic assay prediction. This model outperforms the st
Externí odkaz:
http://arxiv.org/abs/2306.05143
Graphs are widely used to encapsulate a variety of data formats, but real-world networks often involve complex node relations beyond only being pairwise. While hypergraphs and hierarchical graphs have been developed and employed to account for the co
Externí odkaz:
http://arxiv.org/abs/2306.05108
Autor:
Li Zehui
Publikováno v:
Data Science Journal, Vol 1, Iss 2, Pp 238-247 (2006)
China's Natural Resources Database (CNRD) is a comprehensive database, developed to support the research on natural resources, social sustainable development and environmental security in China. This paper intends to introduce the background, content
Externí odkaz:
https://doaj.org/article/dc942ddd77654d52b23b3fb8216c1bda