most citedCompany-as-Tribe: Company Financial Risk Assessment on Tribe-Style Graph with Hierarchical Graph Neural Networks

41 citations · 46 across the 10 of their papers we have counts for

collaborators

10 papers

cs.HC20241 cited

BDAN: Mitigating Temporal Difference Across Electrodes in Cross-Subject Motor Imagery Classification via Generative Bridging Domain

Zhige Chen, Rui Yang, Mengjie Huang +2

Because of "the non-repeatability of the experiment settings and conditions" and "the variability of brain patterns among subjects", the data distributions across sessions and elec…

cs.RO2024

Smart Help: Strategic Opponent Modeling for Proactive and Adaptive Robot Assistance in Households

Zhihao Cao, Zidong Wang, Siwen Xie +2

Despite the significant demand for assistive technology among vulnerable groups (e.g., the elderly, children, and the disabled) in daily tasks, research into advanced AI-driven ass…

cs.IR2024

A Distance Metric Learning Model Based On Variational Information Bottleneck

YaoDan Zhang, Zidong Wang, Ru Jia +1

In recent years, personalized recommendation technology has flourished and become one of the hot research directions. The matrix factorization model and the metric learning model w…

math.DS2024

On Time-Varying Delayed Stochastic Differential Systems with Non-Markovian Switching Parameters

Xinyu Wu, Zidong Wang, Wenlian Lu

This paper focuses on time-varying delayed stochastic differential systems with stochastically switching parameters formulated by a unified switching behavior combining a discrete…

eess.SY20231 cited

Composite Disturbance Filtering: A Novel State Estimation Scheme for Systems With Multi-Source, Heterogeneous, and Isomeric Disturbances

Lei Guo, Wenshuo Li, Yukai Zhu +2

State estimation has long been a fundamental problem in signal processing and control areas. The main challenge is to design filters with ability to reject or attenuate various dis…

cs.LG2023

Learning to simulate partially known spatio-temporal dynamics with trainable difference operators

Xiang Huang, Zhuoyuan Li, Hongsheng Liu +4

Recently, using neural networks to simulate spatio-temporal dynamics has received a lot of attention. However, most existing methods adopt pure data-driven black-box models, which…