- GRAND: Graph Neural Diffusion
- Directional Graph Networks
- Improving Breadth-Wise Backpropagation in Graph Neural Networks helps Learning Long-Range Dependencies
- Optimization of Graph Neural Networks: Implicit Acceleration by Skip Connections and More Depth
- Training Graph Neural Networks with 1000 Layers
- A Unified Lottery Ticket Hypothesis for Graph Neural Networks
- GNNAutoScale: Scalable and Expressive Graph Neural Networks via Historical Embeddings
- On Explainability of Graph Neural Networks via Subgraph Explorations
- Generative Causal Explanations for Graph Neural Networks
- Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity
- Automated Graph Representation Learning with Hyperparameter Importance Explanation
- A Collective Learning Framework to Boost GNN Expressiveness for Node Classification
- Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks
- Breaking the Limits of Message Passing Graph Neural Networks
- Let's Agree to Degree: Comparing Graph Convolutional Networks in the Message-Passing Framework
- Expressive 1-Lipschitz Neural Networks for Robust Multiple Graph Learning against Adversarial Attacks
- Graph Neural Networks Inspired by Classical Iterative Algorithms
- Elastic Graph Neural Networks
- Interpretable Stability Bounds for Spectral Graph Filters
- Information Obfuscation of Graph Neural Networks
- Integrated Defense for Resilient Graph Matching
- Stochastic Iterative Graph Matching
- Deep Latent Graph Matching
- GLSearch: Maximum Common Subgraph Detection via Learning to Search
- From Local Structures to Size Generalization in Graph Neural Networks
- Graph Convolution for Semi-Supervised Classification: Improved Linear Separability and Out-of-Distribution Generalization
- Graph Contrastive Learning Automated
- Self-supervised Graph-level Representation Learning with Local and Global Structure
- Size-Invariant Graph Representations for Graph Classification Extrapolations
- How Framelets Enhance Graph Neural Networks
- GraphDF: A Discrete Flow Model for Molecular Graph Generation
- Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation
- GraphNorm: A Principled Approach to Accelerating Graph Neural Network Training
- Lipschitz Normalization for Self-Attention Layers with Application to Graph Neural Networks
- Towards Open Ad Hoc Teamwork Using Graph-based Policy Learning
- Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks
- Learning Intra-Batch Connections for Deep Metric Learning
- Compositional Video Synthesis with Action Graphs
- Two Heads are Better Than One: Hypergraph-Enhanced Graph Reasoning for Visual Event Ratiocination
- Scalable Optimal Transport in High Dimensions for Graph Distances, Embedding Alignment, and More
- Message Passing Adaptive Resonance Theory for Online Active Semi-supervised Learning
- Persistence Homology for Link Prediction: An Interactive View
- E(n) Equivariant Graph Neural Networks
- Graph Mixture Density Networks
- Z-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series Forecasting
- Recovering AES Keys with a Deep Cold Boot Attack