78 citations · 135 across the 16 of their papers we have counts for
16 papers
Helper Recommendation with seniority control in Online Health Community
Junruo Gao, Chen Ling, Carl Yang +1
Online health communities (OHCs) are forums where patients with similar conditions communicate their experiences and provide moral support. Social support in OHCs plays a crucial r…
Feature Attention Network (FA-Net): A Deep-Learning Based Approach for Underwater Single Image Enhancement
Muhammad Hamza, Ammar Hawbani, Sami Ul Rehman +2
Underwater image processing and analysis have been a hotspot of study in recent years, as more emphasis has been focused to underwater monitoring and usage of marine resources. Com…
Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations
Tong Steven Sun, Yuyang Gao, Shubham Khaladkar +4
The local explanation provides heatmaps on images to explain how Convolutional Neural Networks (CNNs) derive their output. Due to its visual straightforwardness, the method has bee…
Domain Generalization Deep Graph Transformation
Shiyu Wang, Guangji Bai, Qingyang Zhu +2
Graph transformation that predicts graph transition from one mode to another is an important and common problem. Despite much progress in developing advanced graph transformation t…
Deep Graph Representation Learning and Optimization for Influence Maximization
Chen Ling, Junji Jiang, Junxiang Wang +5
Influence maximization (IM) is formulated as selecting a set of initial users from a social network to maximize the expected number of influenced users. Researchers have made great…
Saliency-Augmented Memory Completion for Continual Learning
Guangji Bai, Chen Ling, Yuyang Gao +1
Continual Learning is considered a key step toward next-generation Artificial Intelligence. Among various methods, replay-based approaches that maintain and replay a small episodic…
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning
Yuyang Gao, Siyi Gu, Junji Jiang +3
As the societal impact of Deep Neural Networks (DNNs) grows, the goals for advancing DNNs become more complex and diverse, ranging from improving a conventional model accuracy metr…
DeepGAR: Deep Graph Learning for Analogical Reasoning
Chen Ling, Tanmoy Chowdhury, Junji Jiang +4
Analogical reasoning is the process of discovering and mapping correspondences from a target subject to a base subject. As the most well-known computational method of analogical re…
Multi-objective Deep Data Generation with Correlated Property Control
Shiyu Wang, Xiaojie Guo, Xuanyang Lin +11
Developing deep generative models has been an emerging field due to the ability to model and generate complex data for various purposes, such as image synthesis and molecular desig…
Blockchain-based Medical Image Sharing and Automated Critical-results Notification: A Novel Framework
Jiyoun Randolph, Md Jobair Hossain Faruk, Hossain Shahriar +4
In teleradiology, medical images are transmitted to offsite radiologists for interpretation and the dictation report is sent back to the original site to aid timely diagnosis and p…
Controllable Data Generation by Deep Learning: A Review
Shiyu Wang, Yuanqi Du, Xiaojie Guo +3
Designing and generating new data under targeted properties has been attracting various critical applications such as molecule design, image editing and speech synthesis. Tradition…
Interpretable Molecular Graph Generation via Monotonic Constraints
Yuanqi Du, Xiaojie Guo, Amarda Shehu +1
Designing molecules with specific properties is a long-lasting research problem and is central to advancing crucial domains such as drug discovery and material science. Recent adva…
Disentangled Spatiotemporal Graph Generative Models
Yuanqi Du, Xiaojie Guo, Hengning Cao +2
Spatiotemporal graph represents a crucial data structure where the nodes and edges are embedded in a geometric space and can evolve dynamically over time. Nowadays, spatiotemporal…
Black-box Node Injection Attack for Graph Neural Networks
Mingxuan Ju, Yujie Fan, Yanfang Ye +1
Graph Neural Networks (GNNs) have drawn significant attentions over the years and been broadly applied to vital fields that require high security standard such as product recommend…
Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment
Yuyang Gao, Tong Sun, Liang Zhao +1
While Deep Neural Networks (DNNs) are deriving the major innovations in nearly every field through their powerful automation, we are also witnessing the peril behind automation as…
DT-LET: Deep Transfer Learning by Exploring where to Transfer
Jianzhe Lin, Qi Wang, Rabab Ward +1
Previous transfer learning methods based on deep network assume the knowledge should be transferred between the same hidden layers of the source domain and the target domains. This…