- Revisiting Graph Homophily Measures
- Edge-Splitting MLP: Node Classification on Homophilic and Heterophilic Graphs without Message Passing
- Flexible Diffusion Scopes with Parameterized Laplacian for Heterophilic Graph Learning
- Do We Really Need Complicated Graph Learning Models? -- A Simple but Effective Baseline
- Simple GNNs with Low Rank Non-parametric Aggregators
- Hyperbolic Kernel Convolution: A Generic Framework
- DF-GNN: Dynamic Fusion Framework for Attention Graph Neural Networks on GPUs
- Stochastic Experience-Replay for Graph Continual Learning
- GraTeD-MLP: Efficient Node Classification via Graph Transformer Distillation to MLP
- A Pure Transformer Pretraining Framework on Text-attributed Graphs
- Optimal performance of Graph Convolutional Networks on the Contextual Stochastic Block Model
- Preventing Representational Rank Collapse in MPNNs by Splitting the Computational Graph
- Oversquashing in Hypergraph Neural Networks
- Matrix Completion with Hypergraphs: Sharp Thresholds and Efficient Algorithms
- Leveraging Temporal Graph Networks Using Module Decoupling
- UTG: Towards a Unified View of Snapshot and Event Based Models for Temporal Graphs
- Enhancing Topological Dependencies in Spatio-Temporal Graphs with Cycle Message Passing Blocks
- Scalable and Efficient Temporal Graph Representation Learning via Forward Recent Sampling
- Dynamic Representations of Global Crises: A Temporal Knowledge Graph For Conflicts, Trade and Value Networks
- TRIX: A More Expressive Model for Zero-shot Domain Transfer in Knowledge Graphs
- A Neuro-Symbolic Framework for Answering Graph Pattern Queries in Knowledge Graphs
- Knowledge Graph Preference Contrastive Learning for Recommendation
- Smoothed Graph Contrastive Learning via Seamless Proximity Integration
- Motif-aware Attribute Masking for Molecular Graph Pre-training
- CrysAtom: Distributed Representation of Atoms for Crystal Property Prediction
- A Transferable Graph Autoencoder Framework for Network Alignment
- xAI-Drop: Don't use what you cannot explain
- Ising on the Graph: Task-specific Graph Subsampling via the Ising Model
- On the Expressivity of Persistent Homology in Graph Learning
- CliquePH: Higher-Order Information for Graph Neural Networks through Persistent Homology on Clique Graphs
- Sub-graph Based Diffusion Model for Link Prediction
- Data Augmentation for Supervised Graph Outlier Detection via Latent Diffusion Models
- Towards a GNN Framework for Combinatorial Optimization Problems
- Effectiveness of SDP rounding using Hopfield Networks
- Reinforcement Learning Discovers Efficient Decentralized Graph Path Search Strategies
- Asymptotic generalization error of a single-layer graph convolutional network
- Understanding Feature/Structure Interplay in Graph Neural Networks
- Faster Optimization on Sparse Graphs via Neural Reparametrization
- NP-NDS: A Nature-Powered Nonlinear Dynamical System for Power Grid Forecasting
- Decomposing force fields as flows on graphs reconstructed from stochastic trajectories
- Multi-Scale High-Resolution Logarithmic Grapher Module for Efficient Vision GNNs