94 citations · 137 across the 4 of their papers we have counts for
10 papers
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy
Enyan Dai, Limeng Cui, Zhengyang Wang +5
Graph Neural Networks (GNNs) have achieved great success in modeling graph-structured data. However, recent works show that GNNs are vulnerable to adversarial attacks which can foo…
Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery
Zhengyang Wang, Meng Liu, Youzhi Luo +8
Properties of molecules are indicative of their functions and thus are useful in many applications. With the advances of deep learning methods, computational approaches for predict…
Noise2Same: Optimizing A Self-Supervised Bound for Image Denoising
Yaochen Xie, Zhengyang Wang, Shuiwang Ji
Self-supervised frameworks that learn denoising models with merely individual noisy images have shown strong capability and promising performance in various image denoising tasks.…
Deep Low-Shot Learning for Biological Image Classification and Visualization from Limited Training Samples
Lei Cai, Zhengyang Wang, Rob Kulathinal +2
Predictive modeling is useful but very challenging in biological image analysis due to the high cost of obtaining and labeling training data. For example, in the study of gene inte…
CorDEL: A Contrastive Deep Learning Approach for Entity Linkage
Zhengyang Wang, Bunyamin Sisman, Hao Wei +2
Entity linkage (EL) is a critical problem in data cleaning and integration. In the past several decades, EL has typically been done by rule-based systems or traditional machine lea…
Global Voxel Transformer Networks for Augmented Microscopy
Zhengyang Wang, Yaochen Xie, Shuiwang Ji
Advances in deep learning have led to remarkable success in augmented microscopy, enabling us to obtain high-quality microscope images without using expensive microscopy hardware a…