Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks

15 January 2021

Papers citing "Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks"

38 / 38 papers shown

Title
A Survey on Temporal Interaction Graph Representation Learning: Progress, Challenges, and Opportunities Pengfei Jiao Hongjiang Chen Xuan Guo Zhidong Zhao Dongxiao He Di Jin AI4CE 29 0 0 07 May 2025
Unifying Text Semantics and Graph Structures for Temporal Text-attributed Graphs with Large Language Models Siwei Zhang Yun Xiong Yateng Tang Xi Chen Zian Jia Zehao Gu Jiarong Xu Jiawei Zhang AI4CE 75 1 0 18 Mar 2025
ScaDyG:A New Paradigm for Large-scale Dynamic Graph Learning Xiang Wu Xunkai Li Rong-Hua Li Kangfei Zhao Guoren Wang AI4TS AI4CE 59 0 0 27 Jan 2025
Community-Aware Temporal Walks: Parameter-Free Representation Learning on Continuous-Time Dynamic Graphs He Yu Qingbin Liu 36 0 0 21 Jan 2025
Mind the truncation gap: challenges of learning on dynamic graphs with recurrent architectures Joao Bravo Jacopo Bono Pedro Saleiro Hugo Ferreira P. Bizarro 42 0 0 31 Dec 2024
Towards Ideal Temporal Graph Neural Networks: Evaluations and Conclusions after 10,000 GPU Hours Yuxin Yang Hongkuan Zhou Rajgopal Kannan Viktor Prasanna 43 0 0 31 Dec 2024
HyperBrain: Anomaly Detection for Temporal Hypergraph Brain Networks Sadaf Sadeghian Xiaoxiao Li Margo Seltzer 32 0 0 02 Oct 2024
Retrieval Augmented Generation for Dynamic Graph Modeling Yuxia Wu Lizi Liao Yuan Fang 54 3 0 26 Aug 2024
Efficient Neural Common Neighbor for Temporal Graph Link Prediction Xiaohui Zhang Yanbo Wang Xiyuan Wang Muhan Zhang 36 1 0 12 Jun 2024
Microstructures and Accuracy of Graph Recall by Large Language Models Yanbang Wang Hejie Cui Jon M. Kleinberg 42 2 0 19 Feb 2024
HOT: Higher-Order Dynamic Graph Representation Learning with Efficient Transformers Maciej Besta Afonso Claudino Catarino Lukas Gianinazzi Nils Blach Piotr Nyczyk H. Niewiadomski Torsten Hoefler 35 6 0 30 Nov 2023
New Perspectives on the Evaluation of Link Prediction Algorithms for Dynamic Graphs Raphaël Romero T. D. Bie Jefrey Lijffijt 26 0 0 30 Nov 2023
Temporal Graph Representation Learning with Adaptive Augmentation Contrastive Hongjiang Chen Pengfei Jiao Huijun Tang Huaming Wu 26 8 0 07 Nov 2023
SPEED: Streaming Partition and Parallel Acceleration for Temporal Interaction Graph Embedding Xiangshan Chen Yongxiang Liao Yun Xiong Yao Zhang Si-Yuan Zhang Jiawei Zhang Yiheng Sun 23 6 0 27 Aug 2023
From random-walks to graph-sprints: a low-latency node embedding framework on continuous-time dynamic graphs Ahmad Naser Eddin Jacopo Bono David Oliveira Aparício Hugo Ferreira João Tiago Ascensão Pedro Ribeiro P. Bizarro 37 2 0 17 Jul 2023
DistTGL: Distributed Memory-Based Temporal Graph Neural Network Training Hongkuan Zhou Da Zheng Xiang Song George Karypis Viktor Prasanna GNN 29 13 0 14 Jul 2023
CPDG: A Contrastive Pre-Training Method for Dynamic Graph Neural Networks Yuan-Qi Bei Haonan Xu Sheng Zhou Huixuan Chi Haishuai Wang Mengdi Zhang Zhao Li Jiajun Bu 46 6 0 06 Jul 2023
Deep Temporal Graph Clustering Meng Liu Yue Liu K. Liang Wenxuan Tu Siwei Wang Sihang Zhou Xinwang Liu 35 48 0 18 May 2023
Dynamic Graph Representation Learning with Neural Networks: A Survey Leshanshui Yang Sébastien Adam Clément Chatelain AI4TS AI4CE 39 14 0 12 Apr 2023
Towards Open Temporal Graph Neural Networks Kaituo Feng Changsheng Li Xiaolu Zhang Jun Zhou AI4CE 30 15 0 27 Mar 2023
Towards Better Dynamic Graph Learning: New Architecture and Unified Library Le Yu Leilei Sun Bowen Du Weifeng Lv AI4CE 29 98 0 23 Mar 2023
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning Haoteng Yin Muhan Zhang Jianguo Wang Pan Li 66 8 0 06 Mar 2023
Do We Really Need Complicated Model Architectures For Temporal Networks? Weilin Cong Si Zhang Jian Kang Baichuan Yuan Hao Wu Xin Zhou Hanghang Tong Mehrdad Mahdavi GNN AI4TS 31 114 0 22 Feb 2023
TIGER: Temporal Interaction Graph Embedding with Restarts Yao Zhang Yun Xiong Yongxiang Liao Yiheng Sun Yucheng Jin Xuehao Zheng Yangyong Zhu 22 24 0 13 Feb 2023
Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs Linhao Luo Reza Haffari Shirui Pan AI4TS 28 30 0 15 Nov 2022
TPGNN: Learning High-order Information in Dynamic Graphs via Temporal Propagation Zehong Wang Qi Li Donghua Yu 27 3 0 03 Oct 2022
Provably expressive temporal graph networks Amauri Souza Diego Mesquita Samuel Kaski Vikas K. Garg 89 54 0 29 Sep 2022
De Bruijn goes Neural: Causality-Aware Graph Neural Networks for Time Series Data on Dynamic Graphs Lisi Qarkaxhija Vincenzo Perri Ingo Scholtes CML AI4CE 24 6 0 17 Sep 2022
A Survey on Temporal Graph Representation Learning and Generative Modeling Shubham Gupta Srikanta J. Bedathur AI4TS AI4CE 32 6 0 25 Aug 2022
Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks Jintang Li Zhouxin Yu Zulun Zhu Liang Chen Qi Yu Zibin Zheng Sheng Tian Ruofan Wu Changhua Meng GNN 24 31 0 15 Aug 2022
Representation Learning in Continuous-Time Dynamic Signed Networks Kartik Sharma Mohit Raghavendra Y. Lee M. Anandkumar Srijan Kumar 34 8 0 07 Jul 2022
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs Yangze Zhou Gitta Kutyniok Bruno Ribeiro OODD AI4CE 83 37 0 30 May 2022
TGL: A General Framework for Temporal GNN Training on Billion-Scale Graphs Hongkuan Zhou Da Zheng Israt Nisa Vasileios Ioannidis Xiang Song George Karypis AI4CE 39 86 0 28 Mar 2022
Model-Architecture Co-Design for High Performance Temporal GNN Inference on FPGA Hongkuan Zhou Bingyi Zhang Rajgopal Kannan Viktor Prasanna Carl E. Busart GNN 32 23 0 10 Mar 2022
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks Hongya Wang Haoteng Yin Muhan Zhang Pan Li 35 107 0 01 Mar 2022
Inductive Representation Learning in Temporal Networks via Mining Neighborhood and Community Influences Meng Liu Yong Liu AI4TS 85 37 0 01 Oct 2021
SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings Hongkuan Zhou James Orme-Rogers Rajgopal Kannan Viktor Prasanna AI4TS 39 4 0 09 Sep 2021
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,238 0 24 Jun 2017