3 citations · 13 across the 11 of their papers we have counts for
14 papers
CETransformer: Casual Effect Estimation via Transformer Based Representation Learning
Zhenyu Guo, Shuai Zheng, Zhizhe Liu +2
Treatment effect estimation, which refers to the estimation of causal effects and aims to measure the strength of the causal relationship, is of great importance in many fields but…
Multi-modal Graph Learning for Disease Prediction
Shuai Zheng, Zhenfeng Zhu, Zhizhe Liu +3
Benefiting from the powerful expressive capability of graphs, graph-based approaches have achieved impressive performance in various biomedical applications. Most existing methods…
From Anchor Generation to Distribution Alignment: Learning a Discriminative Embedding Space for Zero-Shot Recognition
Fuzhen Li, Zhenfeng Zhu, Xingxing Zhang +2
In zero-shot learning (ZSL), the samples to be classified are usually projected into side information templates such as attributes. However, the irregular distribution of templates…
To See in the Dark: N2DGAN for Background Modeling in Nighttime Scene
Zhenfeng Zhu, Yingying Meng, Deqiang Kong +3
Due to the deteriorated conditions of \mbox{illumination} lack and uneven lighting, nighttime images have lower contrast and higher noise than their daytime counterparts of the sam…
Distribution-induced Bidirectional Generative Adversarial Network for Graph Representation Learning
Shuai Zheng, Zhenfeng Zhu, Xingxing Zhang +3
Graph representation learning aims to encode all nodes of a graph into low-dimensional vectors that will serve as input of many compute vision tasks. However, most existing algorit…
ProLFA: Representative Prototype Selection for Local Feature Aggregation
Xingxing Zhang, Zhenfeng Zhu, Yao Zhao
Given a set of hand-crafted local features, acquiring a global representation via aggregation is a promising technique to boost computational efficiency and improve task performanc…