2022 ICML 关于图的接收列表

Omni-Granular Ego-Semantic Propagation for Self-Supervised Graph Representation Learning

ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning

Local Augmentation for Graph Neural Networks

G-Mixup: Graph Data Augmentation for Graph Classification

Structural Entropy Guided Graph Hierarchical Pooling

p-Laplacian Based Graph Neural Networks

NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning

HousE: Knowledge Graph Embedding with Householder Parameterization

DSTAGNN: Dynamic Spatial-Temporal Aware Graph Neural Network for Traffic Flow Forecasting

Topology-Aware Network Pruning using Multi-stage Graph Embedding and Reinforcement Learning

Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations

Self-Supervised Representation Learning via Latent Graph Prediction

Large-Scale Graph Neural Architecture Search

Going Deeper into Permutation-Sensitive Graph Neural Networks

Scalable Deep Gaussian Markov Random Fields for General Graphs

Graph Neural Architecture Search Under Distribution Shifts

Faster Fundamental Graph Algorithms via Learned Predictions

Approximate Frank-Wolfe Algorithms over Graph-structured Support Sets

Model-based Meta Reinforcement Learning using Graph Structured Surrogate Models and Amortized Policy Search

Learning to Solve PDE-constrained Inverse Problems with Graph Networks

GNNRank: Learning Global Rankings from Pairwise Comparisons via Directed Graph Neural Networks

Learning to Predict Graphs with Fused Gromov-Wasserstein Barycenters

Deep Variational Graph Convolutional Recurrent Network for Multivariate Time Series Anomaly Detection

The Infinite Contextual Graph Markov Model

Rethinking Graph Neural Networks for Anomaly Detection

Deep Neural Network Fusion via Graph Matching with Applications to Model Ensemble and Federated Learning

Simultaneously Learning Stochastic and Adversarial Bandits with General Graph Feedback

What Dense Graph Do You Need for Self-Attention?

A New Perspective on the Effects of Spectrum in Graph Neural Networks

Deep and Flexible Graph Neural Architecture Search

CN: Graph Gaussian Convolution Networks with Concentrated Graph Filters

Sublinear-Time Clustering Oracle for Signed Graphs

Convergence of Invariant Graph Networks

Finding Global Homophily in Graph Neural Networks When Meeting Heterophily

GALAXY: Graph-based Active Learning at the Extreme

Neural-Symbolic Models for Logical Queries on Knowledge Graphs

Neuron Dependency Graphs: A Causal Abstraction of Neural Networks

A Hierarchical Transitive-Aligned Graph Kernel for Un-attributed Graphs

How Powerful are Spectral Graph Neural Networks

Structure-Aware Transformer for Graph Representation Learning

On the Equivalence Between Temporal and Static Equivariant Graph Representations

Optimization-induced Implicit Graph Diffusion

Self-Organized Polynomial-Time Coordination Graphs

Molecular Graph Representation Learning via Heterogeneous Motif Graph Construction

Let Invariant Rationale Discovery Inspire Graph Contrastive Learning

Equivariant Quantum Graph Circuits

PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs

SPECTRE : Spectral Conditioning Overcomes the Expressivity Limits of One-shot Graph Generators

Efficient low rank convex bounds for pairwise discrete Graphical Model

Comprehensive Analysis of Negative Sampling in Knowledge Graph Representation Learning

A Theoretical Comparison of Graph Neural Network Extensions

A Study on the Ramanujan Graph Property of Winning Lottery Tickets

pathGCN: Learning General Graph Spatial Operators from Paths

Discovering Generalizable Spatial Goal Representations via Graph-based Active Reward Learning

Simultaneous Graph Signal Clustering and Graph Learning

Practical Almost-Linear-Time Approximation Algorithms for Hybrid and Overlapping Graph Clustering

GraphFM: Improving Large-Scale GNN Training via Feature Momentum

Generalization Guarantee of Training Graph Convolutional Networks with Graph Topology Sampling

Information Bottleneck-Guided Stochastic Attention Mechanism for Interpretable Graph Learning

Cross-Space Active Learning on Graph Convolutional Networks

VarScene: A Deep Generative Model for Realistic Scene Graph Synthesis

Boosting Graph Structure Learning with Dummy Nodes