- Neural Structured Prediction for Inductive Node Classification
- GraphENS: Neighbor-Aware Ego Network Synthesis for Class-Imbalanced Node Classification
- Information Gain Propagation: a New Way to Graph Active Learning with Soft Labels
- Why Propagate Alone? Parallel Use of Labels and Features on Graphs
- You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks
- Understanding and Improving Graph Injection Attack by Promoting Unnoticeability
- Graph-less Neural Networks: Teaching Old MLPs New Tricks Via Distillation
- Large-Scale Representation Learning on Graphs via Bootstrapping
- PipeGCN: Efficient Full-Graph Training of Graph Convolutional Networks with Pipelined Feature Communication
- IGLU: Efficient GCN Training via Lazy Updates
- Adaptive Filters for Low-Latency and Memory-Efficient Graph Neural Networks
- Graph Condensation for Graph Neural Networks
- Learn Locally, Correct Globally: A Distributed Algorithm for Training Graph Neural Networks
- EXACT: Scalable Graph Neural Networks Training via Extreme Activation Compression
- Towards Training Billion Parameter Graph Neural Networks for Atomic Simulations
- Towards Deepening Graph Neural Networks: A GNTK-based Optimization Perspective
- Revisiting Over-smoothing in BERT from the Perspective of Graph
- GRAND++: Graph Neural Diffusion with A Source Term
- Understanding over-squashing and bottlenecks on graphs via curvature
- Discovering Invariant Rationales for Graph Neural Networks
- DEGREE: Decomposition Based Explanation for Graph Neural Networks
- Explainable GNN-Based Models over Knowledge Graphs
- Relational Multi-Task Learning: Modeling Relations between Data and Tasks
- Inductive Relation Prediction Using Analogy Subgraph Embeddings
- NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs
- Neural Methods for Logical Reasoning over Knowledge Graphs
- Query Embedding on Hyper-Relational Knowledge Graphs
- Automated Self-Supervised Learning for Graphs
- Self-Supervised Graph Neural Networks for Improved Electroencephalographic Seizure Analysis
- Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction
- A New Perspective on ''How Graph Neural Networks Go Beyond Weisfeiler-Lehman?''
- Expressiveness and Approximation Properties of Graph Neural Networks
- How Attentive are Graph Attention Networks?
- Graph Neural Networks with Learnable Structural and Positional Representations
- PF-GNN: Differentiable particle filtering based approximation of universal graph representations
- Topological Graph Neural Networks
- Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks
- From Stars to Subgraphs: Uplifting Any GNN with Local Structure Awareness
- GLASS: GNN with Labeling Tricks for Subgraph Representation Learning
- Equivariant Subgraph Aggregation Networks
- Frame Averaging for Invariant and Equivariant Network Design
- Top-N: Equivariant Set and Graph Generation without Exchangeability
- Towards Distribution Shift of Node-Level Prediction on Graphs: An Invariance Perspective
- Cold Brew: Distilling Graph Node Representations with Incomplete or Missing Neighborhoods
- Evaluation Metrics for Graph Generative Models: Problems, Pitfalls, and Practical Solutions
- On Evaluation Metrics for Graph Generative Models
- Iterative Refinement Graph Neural Network for Antibody Sequence-Structure Co-design
- Granger causal inference on DAGs identifies genomic loci regulating transcription
- Geometric Transformers for Protein Interface Contact Prediction
- Data-Efficient Graph Grammar Learning for Molecular Generation
- Differentiable Scaffolding Tree for Molecule Optimization
- GeoDiff: A Geometric Diffusion Model for Molecular Conformation Generation
- An Autoregressive Flow Model for 3D Molecular Geometry Generation from Scratch
- Spatial Graph Attention and Curiosity-driven Policy for Antiviral Drug Discovery
- MoReL: Multi-omics Relational Learning
- Chemical-Reaction-Aware Molecule Representation Learning
- Learning to Extend Molecular Scaffolds with Structural Motifs
- Spanning Tree-based Graph Generation for Molecules
- Learning 3D Representations of Molecular Chirality with Invariance to Bond Rotations
- Spherical Message Passing for 3D Molecular Graphs
- Crystal Diffusion Variational Autoencoder for Periodic Material Generation
- Pre-training Molecular Graph Representation with 3D Geometry
- Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond
- TAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series Forecasting
- Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future
- Filling the Gaps: Multivariate Time Series Imputation by Graph Neural Networks
- Neural graphical modelling in continuous-time: consistency guarantees and algorithms
- Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series
- Graph-Guided Network for Irregularly Sampled Multivariate Time Series
- Learning the Dynamics of Physical Systems from Sparse Observations with Finite Element Networks
- Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions
- Predicting Physics in Mesh-reduced Space with Temporal Attention
- Constrained Graph Mechanics Networks
- Space-Time Graph Neural Networks
- Learning to Remember Patterns: Pattern Matching Memory Networks for Traffic Forecasting
- Neural Models for Output-Space Invariance in Combinatorial Problems
- Whats Wrong with Deep Learning in Tree Search for Combinatorial Optimization
- Graph Neural Network Guided Local Search for the Traveling Salesperson Problem
- Learning Object-Oriented Dynamics for Planning from Text
- GNN is a Counter? Revisiting GNN for Question Answering
- GNN-LM: Language Modeling based on Global Contexts via GNN
- GreaseLM: Graph REASoning Enhanced Language Models
- Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space
- Rethinking Network Design and Local Geometry in Point Cloud: A Simple Residual MLP Framework
- Transform2Act: Learning a Transform-and-Control Policy for Efficient Agent Design
- Context-Aware Sparse Deep Coordination Graphs
- Structure-Aware Transformer Policy for Inhomogeneous Multi-Task Reinforcement Learning
- Know Your Action Set: Learning Action Relations for Reinforcement Learning
- A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Imaging Phenotypes of Disease
- Using Graph Representation Learning with Schema Encoders to Measure the Severity of Depressive Symptoms
- LEARNING GUARANTEES FOR GRAPH CONVOLUTIONAL NETWORKS ON THE STOCHASTIC BLOCK MODEL
- Generalized Demographic Parity for Group Fairness
- Message Passing Neural PDE Solvers
- Convergent Boosted Smoothing for Modeling GraphData with Tabular Node Features
- Convergent Graph Solvers
- Neural Relational Inference with Node-Specific Information
- Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction
- Triangle and Four Cycle Counting with Predictions in Graph Streams
- Learning to Schedule Learning rate with Graph Neural Networks
- Learning Scenario Representation for Solving Two-stage Stochastic Integer Programs