Gravity-Inspired Graph Autoencoders for Directed Link Prediction

23 May 2019

Papers citing "Gravity-Inspired Graph Autoencoders for Directed Link Prediction"

9 / 9 papers shown

Title
A Generative Framework for Predictive Modeling of Multiple Chronic Conditions Using Graph Variational Autoencoder and Bandit-Optimized Graph Neural Network Julian Carvajal Rico A. Alaeddini Syed Hasib Akhter Faruqui S. Fisher-Hoch J. McCormick 63 0 0 13 Mar 2025
Understanding the Design Principles of Link Prediction in Directed Settings Jun Zhai Muberra Ozmen Thomas Markovich AI4CE 31 0 0 24 Feb 2025
Reasoning-Enhanced Healthcare Predictions with Knowledge Graph Community Retrieval Pengcheng Jiang Cao Xiao Minhao Jiang Parminder Bhatia Taha A. Kass-Hout Jimeng Sun Jiawei Han RALM AI4MH 39 4 0 06 Oct 2024
Signed Graph Autoencoder for Explainable and Polarization-Aware Network Embeddings Nikolaos Nakis Chrysoula Kosma Giannis Nikolentzos Michalis Chatzianastasis Iakovos Evdaimon Michalis Vazirgiannis 28 1 0 16 Sep 2024
Origin-Destination Network Generation via Gravity-Guided GAN Can Rong Huandong Wang Yong Li 11 5 0 06 Jun 2023
Rethinking the positive role of cluster structure in complex networks for link prediction tasks Shan-Shan Zhang Wenjiao Zhang Zhan Bu 14 0 0 04 Nov 2022
Directed Graph Auto-Encoders Georgios Kollias Vasileios Kalantzis Tsuyoshi Idé A. Lozano Naoki Abe BDL GNN 20 34 0 25 Feb 2022
A Systematic Survey on Deep Generative Models for Graph Generation Xiaojie Guo Liang Zhao MedIm 10 145 0 13 Jul 2020
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 211 1,329 0 12 Feb 2018