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
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