Graph Inference

Graph inference focuses on extracting meaningful information and relationships from graph-structured data, aiming to improve prediction accuracy and efficiency in various applications. Current research emphasizes developing scalable and efficient algorithms, particularly focusing on Graph Neural Networks (GNNs) and their adaptations like layer-wise inference and node-adaptive propagation methods to overcome computational limitations, especially for large-scale graphs. These advancements are crucial for tackling real-world problems across diverse fields, including anomaly detection, financial modeling, and visual question answering, where efficient and accurate graph analysis is essential. Furthermore, research is actively exploring methods to improve robustness against noisy or adversarial data and to incorporate metadata for richer representations.

Papers

October 30, 2024

Symbolic Graph Inference for Compound Scene Understanding
FNU Aryan, Simon Stepputtis, Sarthak Bhagat, Joseph Campbell, Kwonjoon Lee, Hossein Nourkhiz Mahjoub, Katia Sycara
Domain Knowledge Scene Understanding Scene Structure Graph Search Graph Inference

October 13, 2024

Scalable Weibull Graph Attention Autoencoder for Modeling Document Networks
Chaojie Wang, Xinyang Liu, Dongsheng Wang, Hao Zhang, Bo Chen, Mingyuan Zhou
Network Programming Graph Attention Topic Model Variational Graph RelAtion Network Graph Inference Model Documentation

February 14, 2024

SimMLP: Training MLPs on Graphs without Supervision
Zehong Wang, Zheyuan Zhang, Chuxu Zhang, Yanfang Ye
Graph Neural Network Graph Drawing Graph Learning Task Multi Layer Perceptron Large Scale Graph Datasets Graph Inference

January 6, 2024

GLISP: A Scalable GNN Learning System by Exploiting Inherent Structural Properties of Graphs
Zhongshu Zhu, Bin Jing, Xiaopei Wan, Zhizhen Liu, Lei Liang, Jun zhou
Graph Neural Network Graph Drawing Graph Partitioning Graph Learning Model Graph Cut Structural Characterization Graph Inference Scalable GNN

November 13, 2023

ADAMM: Anomaly Detection of Attributed Multi-graphs with Metadata: A Unified Neural Network Approach
Konstantinos Sotiropoulos, Lingxiao Zhao, Pierre Jinghong Liang, Leman Akoglu
Graph Neural Network Anomaly Detection Metadata Information Graph Inference Unified Neural

October 17, 2023

Accelerating Scalable Graph Neural Network Inference with Node-Adaptive Propagation
Xinyi Gao, Wentao Zhang, Junliang Yu, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin
Graph Inference Inference Acceleration Adaptive Propagation Scalable Graph Neural Network Graph Neural Network Inference

October 13, 2023

Exploring Sparse Spatial Relation in Graph Inference for Text-Based VQA
Sheng Zhou, Dan Guo, Jia Li, Xun Yang, Meng Wang
Visual Relation Spatial Relation Adaptive Graph Graph Inference Page Document VQA Sparse Token

September 6, 2023

Blink: Link Local Differential Privacy in Graph Neural Networks via Bayesian Estimation
Xiaochen Zhu, Vincent Y. F. Tan, Xiaokui Xiao
Graph Neural Network Local Differential Privacy Privacy Budget Bayesian Estimation Graph Inference

July 24, 2023

Addressing the Impact of Localized Training Data in Graph Neural Networks
Akansha A
Graph Neural Network Global Impact Semi Supervised Graph Structured Data Semi Supervised Node Classification Local Datasets Graph Inference

July 1, 2023

InferTurbo: A Scalable System for Boosting Full-graph Inference of Graph Neural Network over Huge Graphs
Dalong Zhang, Xianzheng Song, Zhiyang Hu, Yang Li, Miao Tao, Binbin Hu, Lin Wang, Zhiqiang Zhang, Jun Zhou
Graph Neural Network Inference Task GNN Inference Graph Inference Scalable Architecture

May 28, 2023

ChatGPT Informed Graph Neural Network for Stock Movement Prediction
Zihan Chen, Lei Nico Zheng, Cheng Lu, Jialu Yuan, Di Zhu
Graph Neural Network Network Inference Stock Movement Prediction Graph Inference

November 28, 2022

DGI: Easy and Efficient Inference for GNNs
Peiqi Yin, Xiao Yan, Jinjing Zhou, Qiang Fu, Zhenkun Cai, James Cheng, Bo Tang, Minjie Wang
Graph Neural Network Efficient Inference Inference System Graph Inference GNN Inference

November 21, 2022

Structural Optimization of Factor Graphs for Symbol Detection via Continuous Clustering and Machine Learning
Lukas Rapp, Luca Schmid, Andrej Rode, Laurent Schmalen
Machine Learning Factor Graph Symbol Detection Graph Inference Structural Optimization

November 1, 2022

Efficient Graph Neural Network Inference at Large Scale
Xinyi Gao, Wentao Zhang, Yingxia Shao, Quoc Viet Hung Nguyen, Bin Cui, Hongzhi Yin
Large Scale Large Scale Graph Graph Inference Inference Speedup Scalable Graph Neural Network Graph Neural Network Inference Personalized Propagation

August 20, 2022

Adversarial contamination of networks in the setting of vertex nomination: a new trimming method
Sheyda Peyman, Minh Tang, Vince Lyzinski
Network Programming Graph Data Goal Vertex Spectral Embedding Graph Inference Writer Independent Setting

March 7, 2022

Multivariate Time Series Forecasting with Latent Graph Inference
Victor Garcia Satorras, Syama Sundar Rangapuram, Tim Januschowski
Multivariate Time Series Forecasting Forecasting Performance Graph Inference Latent Graph Inference

December 14, 2021

Neighborhood Random Walk Graph Sampling for Regularized Bayesian Graph Convolutional Neural Networks
Aneesh Komanduri, Justin Zhan
Graph Neural Network Graph Based Semi Supervised Node Classification Graph Sampling Graph Inference