- Decoupling the Depth and Scope of Graph Neural Networks
- Node Dependent Local Smoothing for Scalable Graph Learning
- A Biased Graph Neural Network Sampler with Near-Optimal Regret
- VQ-GNN: A Universal Framework to Scale up Graph Neural Networks using Vector Quantization
- Snowflake: Scaling GNNs to high-dimensional continuous control via parameter freezing
- On Provable Benefits of Depth in Training Graph Convolutional Networks
- Dirichlet Energy Constrained Learning for Deep Graph Neural Networks
- EIGNN: Efficient Infinite-Depth Graph Neural Networks
- Representing Long-Range Context for Graph Neural Networks with Global Attention
- Dissecting the Diffusion Process in Linear Graph Convolutional Networks
- Implicit SVD for Graph Representation Learning
- Robustness of Graph Neural Networks at Scale
- Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration
- Not All Low-Pass Filters are Robust in Graph Convolutional Networks
- Graph Neural Networks with Adaptive Residual
- Topological Relational Learning on Graphs
- Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
- Universal Graph Convolutional Networks
- Diverse Message Passing for Attribute with Heterophily
- Subgroup Generalization and Fairness of Graph Neural Networks
- Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach
- Adaptive Diffusion in Graph Neural Networks
- Discrete-Valued Neural Communication
- Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks
- Reinforcement Learning Enhanced Explainer for Graph Neural Networks
- Towards Multi-Grained Explainability for Graph Neural Networks
- Robust Counterfactual Explanations on Graph Neural Networks
- DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks
- More Powerful Graph Neural Networks with Nesting
- Weisfeiler and Lehman Go Cellular: CW Networks
- Neural Trees for Learning on Graphs
- Reconstruction for Powerful Graph Representations
- Automorphic Equivalence-aware Graph Neural Network
- Graph Neural Networks with Local Graph Parameters
- On the Universality of Graph Neural Networks on Large Random Graphs
- E(n) Equivariant Normalizing Flows
- Automatic Symmetry Discovery with Lie Algebra Convolutional Network
- Contrastive Laplacian Eigenmaps
- Digraph Contrastive Learning
- Contrastive Graph Poisson Networks: Semi-Supervised Learning with Extremely Limited Labels
- Disentangled Contrastive Learning on Graphs
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning
- InfoGCL: Information-Aware Graph Contrastive Learning
- From Canonical Correlation Analysis to Self-supervised Graph Neural Networks
- Multi-view Contrastive Graph Clustering
- Metropolis-Hastings Data Augmentation for Graph Neural Networks
- Adaptive Data Augmentation on Temporal Graphs
- Graph Neural Networks for Link Prediction: A Theoretical Perspective
- Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
- Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction
- GemNet: Universal Directional Graph Neural Networks for Molecules
- Directional Message Passing on Molecular Graphs via Synthetic Coordinates
- GeoMol: Torsional Geometric Generation of Molecular 3D Conformer Ensembles
- Autobahn: Automorphism-based Graph Neural Nets
- Predicting Molecular Conformation via Dynamic Graph Score Matching
- Multi-Scale Representation Learning on Proteins
- Motif-based Graph Self-Supervised Learning for Molecular Property Prediction
- Property-aware Adaptive Relation Networks for Molecular Property Prediction
- Towards understanding retrosynthesis by energy-based models
- Learning Graph Models for Retrosynthesis Prediction
- Topology-Imbalance Learning for Semi-Supervised Node Classification
- Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training data
- Edge Representation Learning with Hypergraphs
- Transformers Generalize DeepSets and Can be Extended to Graphs & Hypergraphs
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization
- INDIGO: GNN-Based Inductive Knowledge Graph Completion Using Pair-Wise Encoding
- Distilling Meta Knowledge on Heterogeneous Graph for Illicit Drug Trafficker Detection on Social Media
- Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation
- Topic Modeling Revisited: A Document Graph-based Neural Network Perspective
- SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL
- Systematic Generalization with Edge Transformers
- Rethinking Graph Transformers with Spectral Attention
- Do Transformers Really Perform Bad for Graph Representation?
- GraphFormers: GNN-nested Transformers for Representation Learning on Textual Graph
- NN-Baker: A Neural-network Infused Algorithmic Framework for Optimization Problems on Geometric Intersection Graphs
- NeuroLKH: Combining Deep Learning Model with Lin-Kernighan-Helsgaun Heuristic for Solving the Traveling Salesman Problem
- Neural Production Systems
- Coupled Segmentation and Edge Learning via Dynamic Graph Propagation
- Coarse-to-fine Animal Pose and Shape Estimation
- TestRank: Bringing Order into Unlabeled Test Instances for Deep Learning Tasks
- MOMA: Multi-Object Multi-Actor Activity Parsing
- Adversarially Robust 3D Point Cloud Recognition Using Self-Supervisions
- Garment4D: Garment Reconstruction from Point Cloud Sequences
- Knowledge-inspired 3D Scene Graph Prediction in Point Cloud
- You Only Look at Text: A CNN-Free Object Detector for Vector Graphics
- Object DGCNN: 3D Object Detection using Dynamic Graphs
- Discovering Dynamic Salient Regions for Spatio-Temporal Graph Neural Networks
- Learning Dynamic Graph Representation of Brain Connectome with Spatio-Temporal Attention
- NeuroMLR: Robust & Reliable Route Recommendation on Road Networks
- GRIN: Generative Relation and Intention Network for Multi-agent Trajectory Prediction
- Exploring Social Posterior Collapse in Variational Autoencoder for Interaction Modeling
- SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
- Graph Differentiable Architecture Search with Structure Learning
- Learning to Learn Graph Topologies
- AutoGEL: An Automated Graph Neural Network with Explicit Link Information
- Parameter Prediction for Unseen Deep Architectures
- Accurately Solving Rod Dynamics with Graph Learning
- Particle Cloud Generation with Message Passing Generative Adversarial Networks
- PDE-GCN: Novel Architectures for Graph Neural Networks Motivated by Partial Differential Equations
- Beltrami Flow and Neural Diffusion on Graphs
- Subgraph Federated Learning with Missing Neighbor Generation
- Federated Graph Classification over Non-IID Graphs
- Permutation-Invariant Variational Autoencoder for Graph-Level Representation Learning
- Learning Compact Representations of Neural Networks using DiscriminAtive Masking (DAM)
- Neural Algorithmic Reasoners are Implicit Planners
- Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation
- MagNet: A Neural Network for Directed Graphs
- Graph Posterior Network: Bayesian Predictive Uncertainty for Node Classification
- A Convergence Analysis of Gradient Descent on Graph Neural Networks
- Ultrahyperbolic Neural Networks
- Alignment Attention by Matching Key and Query Distributions
- Learning Conjoint Attentions for Graph Neural Nets
- BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation
- Deconvolutional Networks on Graph Data
- Learning to Elect
- Roto-translated Local Coordinate Frames For Interacting Dynamical Systems
- RIM: Reliable Influence-based Active Learning on Graphs
- Reducing Collision Checking for Sampling-Based Motion Planning Using Graph Neural Networks
- Learning Semantic Representations to Verify Hardware Designs
- KS-GNN: Keywords Search over Incomplete Graphs via Graphs Neural Network
- Scaling Gaussian Processes with Derivative Information Using Variational Inference
- Solving Graph-based Public Goods Games with Tree Search and Imitation Learning
- Learning Graph Cellular Automata