Zobrazeno 1 - 10
of 1 906
pro vyhledávání: '"Yao Jianhua"'
This paper introduces a novel approach to stock data analysis by employing a Hierarchical Graph Neural Network (HGNN) model that captures multi-level information and relational structures in the stock market. The HGNN model integrates stock relations
Externí odkaz:
http://arxiv.org/abs/2412.06862
This paper takes the graph neural network as the technical framework, integrates the intrinsic connections between enterprise financial indicators, and proposes a model for enterprise credit risk assessment. The main research work includes: Firstly,
Externí odkaz:
http://arxiv.org/abs/2409.17909
Financial fraud refers to the act of obtaining financial benefits through dishonest means. Such behavior not only disrupts the order of the financial market but also harms economic and social development and breeds other illegal and criminal activiti
Externí odkaz:
http://arxiv.org/abs/2409.09892
Multimodal sentiment analysis aims to effectively integrate information from various sources to infer sentiment, where in many cases there are no annotations for unimodal labels. Therefore, most works rely on multimodal labels for training. However,
Externí odkaz:
http://arxiv.org/abs/2408.16029
Incorporating Euclidean symmetries (e.g. rotation equivariance) as inductive biases into graph neural networks has improved their generalization ability and data efficiency in unbounded physical dynamics modeling. However, in various scientific and e
Externí odkaz:
http://arxiv.org/abs/2406.16295
Autor:
Feng, Kehua, Ding, Keyan, Wang, Weijie, Zhuang, Xiang, Wang, Zeyuan, Qin, Ming, Zhao, Yu, Yao, Jianhua, Zhang, Qiang, Chen, Huajun
Large language models (LLMs) have gained increasing prominence in scientific research, but there is a lack of comprehensive benchmarks to fully evaluate their proficiency in understanding and mastering scientific knowledge. To address this need, we i
Externí odkaz:
http://arxiv.org/abs/2406.09098
Autor:
Zhang, Yikun, Ye, Geyan, Yuan, Chaohao, Han, Bo, Huang, Long-Kai, Yao, Jianhua, Liu, Wei, Rong, Yu
Molecule-and-text cross-modal representation learning has emerged as a promising direction for enhancing the quality of molecular representation, thereby improving performance in various scientific fields, including drug discovery and materials scien
Externí odkaz:
http://arxiv.org/abs/2404.16880
Autor:
Yuan, Chaohao, Li, Songyou, Ye, Geyan, Zhang, Yikun, Huang, Long-Kai, Huang, Wenbing, Liu, Wei, Yao, Jianhua, Rong, Yu
The core challenge of de novo protein design lies in creating proteins with specific functions or properties, guided by certain conditions. Current models explore to generate protein using structural and evolutionary guidance, which only provide indi
Externí odkaz:
http://arxiv.org/abs/2404.16866
The decoder-only Transformer architecture with causal masking and relative position encoding (RPE) has become the de facto choice in language modeling. Despite its exceptional performance across various tasks, we have identified two limitations: Firs
Externí odkaz:
http://arxiv.org/abs/2402.04779