GNN-Theory-Papers

This repository mainly lists some the latest research on graph neural network theory.

Table of Contents

Survey

Spectral Domains

Spatial Domains

Expressive Power

Dynamic Graph

Application

Survey

Name	Paper	Venue	Year	Code	Hint
Survey	A Comprehensive Survey on Graph Neural Networks	arxiv	2019
Survey	Graph neural networks: A review of methods and applications	ScienceDirect	2020
Survey	Bridging the Gap between Spatial and Spectral Domains: A Survey on Graph Neural Networks	arxiv	2020

Spectral Domains

Name	Paper	Venue	Year	Code	Hint
	Spectral Networks and Deep Locally Connected Networks on Graphs	arxiv	2013
	Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering	NIPS	2016
GCN	SEMI-SUPERVISED CLASSIFICATION WITH GRAPH CONVOLUTIONAL NETWORKS	ICLR	2017	Pytorch
BernNet	BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation	arxiv	2019	Pytorch
GPR-GNN	ADAPTIVE UNIVERSAL GENERALIZED PAGERANK GRAPH NEURAL NETWORK	ICLR	2021	Pytorch
EvenNet	EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks	NIPS	2022	Code
	How Powerful are Spectral Graph Neural Networks	ICLR	2022
FavardGNN	Graph Neural Networks with Learnable and Optimal Polynomial Bases	arxiv	2023	Pytorch
LON-GNN	LON-GNN: Spectral GNNs with Learnable Orthonormal Basis	arxiv	2023	Pytorch

Spatial Domains

Name	Paper	Venue	Year	Code	Hint
MPNNs	Neural Message Passing for Quantum Chemistry	arxiv	2017
SGC	Simplifying Graph Convolutional Networks	ICML	2019
	Can Graph Neural Networks Count Substructures?	NIPS	2020	Code
GNNML3	Breaking the Limits of Message Passing Graph Neural Networks	ICML	2021
	MESSAGE PASSING ALL THE WAY UP	arxiv	2022
	Shortest Path Networks for Graph Property Prediction	arxiv	2022
	Towards Training GNNs using Explanation Directed Message Passing	ICLR	2022
	ANISOTROPIC MESSAGE PASSING: GRAPH NEURAL NETWORKS WITH DIRECTIONAL AND LONG-RANGE INTERACTIONS	ICLR	2023
	FUNDAMENTAL LIMITS IN FORMAL VERIFICATION OF MESSAGE-PASSING NEURAL NETWORKS	ICLR	2023

Expressive Power

Name	Paper	Venue	Year	Code	Hint
	Wasserstein Weisfeiler-Lehman Graph Kernels	JMLR	2011
k-GNNs	Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks	arxiv	2018
GIN	How Powerful are Graph Neural Networks?	ICLR	2019	Pytorch
	Graph Neural Networks are Dynamic Programmers	arxiv	2019
	Stability and Generalization of Graph Convolutional Neural Networks	arxiv	2019
	Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology	arxiv	2019	Pytorch
	GRAPH NEURAL NETWORKS EXPONENTIALLY LOSE EXPRESSIVE POWER FOR NODE CLASSIFICATION	ICLR	2020	Code
GNN-AK	FROM STARS TO SUBGRAPHS: UPLIFTING ANY GNN WITH LOCAL STRUCTURE AWARENESS	ICLR	2022	Pytorch
GraphSNN	A NEW PERSPECTIVE ON "HOW GRAPH NEURAL NETWORKS GO BEYOND WEISFEILER-LEHMAN?"	ICLR	2022	Pytorch
KP-GNN	How Powerful are K-hop Message Passing Graph Neural Networks	ICLR	2022	Pytorch
	Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction	arxiv	2022
	Efficiently Counting Substructures by Subgraph GNNs without Running GNN on Subgraphs	arxiv	2023
	Improving Expressivity of Graph Neural Networks using Localization	arxiv	2023	Pytorch
	Approximately Equivariant Graph Networks	arxiv	2023	Pytorch
	How Faithful are Self-Explainable GNNs?	arxiv	2023
	Generalizing Topological Graph Neural Networks with Paths	arxiv	2023
N2GNN	Towards Arbitrarily Expressive GNNs in O(n2) Space by Rethinking Folklore Weisfeiler-Lehman	ICLR	2023	Pytorch
I2GNN	BOOSTING THE CYCLE COUNTING POWER OF GRAPH NEURAL NETWORKS WITH I2 -GNNS	ICLR	2023	Pytorch
VQGRAPH	VQGRAPH: Graph Vector-Quantization for Bridging GNNs and MLPs	arxiv	2023	Pytorch

Dynamic Graph

Name	Paper	Venue	Year	Code	Hint
Survey	Foundations and Modeling of Dynamic Networks Using Dynamic Graph Neural Networks: A Survey	IEEE Access	2021
Survey	Encoder-Decoder Architecture for Supervised Dynamic Graph Learning: A Survey	arxiv	2022
	Information Theoretically Optimal Sample Complexity of Learning Dynamical Directed Acyclic Graphs	arxiv	2023
	Reversible and irreversible bracket-based dynamics for deep graph neural networks	arxiv	2023
PIGNN	Continual Learning on Dynamic Graphs via Parameter Isolation	arxiv	2023
	Analysis of different temporal graph neural network configurations on dynamic graphs	arxiv	2023
		arxiv	2023

Application

Name	Paper	Venue	Year	Code	Hint
TGC	How Expressive are Spectral-Temporal Graph Neural Networks for Time Series Forecasting?		arxiv	2023
RDGT	Recurrent Transformer for Dynamic Graph Representation Learning with Edge Temporal States		arxiv	2023
Auto-HeG	Auto-HeG: Automated Graph Neural Network on Heterophilic Graphs		arxiv	2023