awesome-graph-research-icml2024
github.com/azminewasi/awesome-graph-research-icml2024 ↗All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.
236
GitHub Stars
246
Curated Resources
14
Categories
23 hours ago
Last Refreshed
GNN TheoriesGNNs for PDE/ODE/PhysicsGraph and Large Language Models/AgentsKnowledge Graph and Knowledge Graph EmbeddingsSpatial and/or Temporal GNNsGNN ApplicationsExplainable AIReinforcement LearningGraphs and MoleculesGFlowNetsCasual Discovery and GraphsFederated Learning, Privacy, DecentralizationScene GraphsMore Collectons:
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me diffusion resources from awesome-graph-research-icml2024"
Installation instructions →What's inside
GNN Applications
- A Circuit Domain Generalization Framework for Efficient Logic Synthesis in Chip Design
- Biharmonic Distance of Graphs and its Higher-Order Variants: Theoretical Properties with Applications to Centrality and Clustering
- Bringing Motion Taxonomies to Continuous Domains via GPLVM on Hyperbolic manifolds
- CARTE: Pretraining and Transfer for Tabular Learning
- Graph2Tac: Online Representation Learning of Formal Math Concepts
- LaMAGIC: Language-Model-based Topology Generation for Analog Integrated Circuits
Casual Discovery and Graphs
- Adaptive Online Experimental Design for Causal Discovery
- A Fixed-Point Approach for Causal Generative Modeling
- Causal Discovery with Fewer Conditional Independence Tests
- Causal Effect Identification in LiNGAM Models with Latent Confounders
- Causal-IQA: Towards the Generalization of Image Quality Assessment Based on Causal Inference
- Causal Representation Learning from Multiple Distributions: A General Setting
GNN Theories
- A Graph is Worth $K$ Words: Euclideanizing Graph using Pure TransformerDiffusion
- Aligning Transformers with Weisfeiler-LemanDiffusion
- A Near-Linear Time Approximation Algorithm for Beyond-Worst-Case Graph ClusteringDiffusion
- An Efficient Maximal Ancestral Graph Listing AlgorithmDiffusion
- An Empirical Study of Realized GNN Expressiveness
- Automated Loss function Search for Class-imbalanced Node ClassificationDiffusion
More Collectons:
Federated Learning, Privacy, Decentralization
Reinforcement Learning
Graph and Large Language Models/Agents
- Case-Based or Rule-Based: How Do Transformers Do the Math?
- GPTSwarm: Language Agents as Optimizable Graphs
- Graph-enhanced Large Language Models in Asynchronous Plan Reasoning
- LLaGA: Large Language and Graph Assistant
- MAGDi: Structured Distillation of Multi-Agent Interaction Graphs Improves Reasoning in Smaller Language Models
Graphs and Molecules
- CHEMREASONER: Heuristic Search over a Large Language Models Knowledge Space using Quantum-Chemical Feedback
- Expressivity and Generalization: Fragment-Biases for Molecular GNNs
- Gaussian Plane-Wave Neural Operator for Electron Density Estimation
- Generalist Equivariant Transformer Towards 3D Molecular Interaction Learning
- Modelling Microbial Communities with Graph Neural Networks
- Projecting Molecules into Synthesizable Chemical Spaces
Showing a sample of 246 resources. View the full list on GitHub →