9 citations · 21 across the 7 of their papers we have counts for
8 papers
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…
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…