Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement

Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement

9 June 2020

Papers citing "Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement"

11 / 11 papers shown

Title
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation Kexin Zhang Shuhan Liu Song Wang Weili Shi Chen Chen Pan Li Sheng R. Li Jundong Li Kaize Ding OOD 45 2 0 25 Oct 2024
Disentangled Representation Learning Xin Eric Wang Hong Chen Siao Tang Zihao Wu Wenwu Zhu DRL 19 77 0 21 Nov 2022
Multi-objective Deep Data Generation with Correlated Property Control Shiyu Wang Xiaojie Guo Xuanyang Lin Bo Pan Yuanqi Du ... S. Alkhalifa K. Minbiole Bill Wuest Amarda Shehu Liang Zhao AI4CE 42 14 0 01 Oct 2022
Controllable Data Generation by Deep Learning: A Review Shiyu Wang Yuanqi Du Xiaojie Guo Bo Pan Zhaohui Qin Liang Zhao 29 28 0 19 Jul 2022
A Survey on Deep Graph Generation: Methods and Applications Yanqiao Zhu Yuanqi Du Yinkai Wang Yichen Xu Jieyu Zhang Qiang Liu Shu Wu 3DV GNN 26 67 0 13 Mar 2022
Disentangled Spatiotemporal Graph Generative Models Yuanqi Du Xiaojie Guo Hengning Cao Yanfang Ye Liang Zhao 16 20 0 28 Feb 2022
Aligning Eyes between Humans and Deep Neural Network through Interactive Attention Alignment Yuyang Gao Tong Sun Liang Zhao Sungsoo Ray Hong HAI 13 37 0 06 Feb 2022
A Systematic Survey on Deep Generative Models for Graph Generation Xiaojie Guo Liang Zhao MedIm 26 145 0 13 Jul 2020
Deep Multi-attributed Graph Translation with Node-Edge Co-evolution Xiaojie Guo Liang Zhao Cameron Nowzari S. Rafatirad Houman Homayoun Sai Manoj Pudukotai Dinakarrao 37 27 0 22 Mar 2020
Building machines that adapt and compute like brains Brenden Lake J. Tenenbaum AI4CE FedML NAI AILaw 243 891 0 11 Nov 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,672 0 28 Feb 2017