- Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case
- Generalization and Representational Limits of Graph Neural Networks
- Constant Curvature Graph Convolutional Networks
- Differentiating through the Fréchet Mean
- Latent Variable Modelling with Hyperbolic Normalizing Flows
- Simple and Deep Graph Convolutional Networks
- Bayesian Graph Neural Networks with Adaptive Connection Sampling
- Continuous Graph Neural Networks
- Efficient Robustness Certificates for Discrete Data: Sparsity-Aware Randomized Smoothing for Graphs, Images and More
- Robust Graph Representation Learning via Neural Sparsification
- When Does Self-Supervision Help Graph Convolutional Networks?
- Contrastive Multi-View Representation Learning on Graphs
- Graph-based, Self-Supervised Program Repair from Diagnostic Feedback
- Generating Programmatic Referring Expressions via Program Synthesis
- Deep Graph Random Process for Relational-Thinking-Based Speech Recognition
- Generalized Neural Policies for Relational MDPs
- Inductive Relation Prediction by Subgraph Reasoning
- GraphOpt: Learning Optimization Models of Graph Formation
- Few-shot Relation Extraction via Bayesian Meta-learning on Task Graphs
- Graph Convolutional Network for Recommendation with Low-pass Collaborative Filters
- Semiparametric Nonlinear Bipartite Graph Representation Learning with Provable Guarantees
- Progressive Graph Learning for Open-Set Domain Adaptation
- Incidence Networks for Geometric Deep Learning
- Convolutional Kernel Networks for Graph-Structured Data
- Spectral Clustering with Graph Neural Networks for Graph Pooling
- Haar Graph Pooling
- Graph Homomorphism Convolution
- Graph Filtration Learning
- Distance-Preserving Graph Embeddings from Random Neural Features
- GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation
- A Graph to Graphs Framework for Retrosynthesis Prediction
- Multi-Objective Molecule Generation using Interpretable Substructures
- Hierarchical Generation of Molecular Graphs using Structural Motifs
- Deep Coordination Graphs
- One Policy to Control Them All: Shared Modular Policies for Agent-Agnostic Control
- Multi-Agent Routing Value Iteration Network
- Learning to Simulate Complex Physics with Graph Networks
- Learning to Simulate and Design for Structural Engineering
- Combining Differentiable PDE Solvers and Graph Neural Networks for Fluid Flow Prediction
- Interferometric Graph Transform: a Deep Unsupervised Graph Representation
- Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation
- Graph Structure of Neural Networks
- Learning Algebraic Multigrid Using Graph Neural Networks
- LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction