PROTEINS

Overview edit

Variants: PROTEINS

Associated Benchmarks

This dataset is used in 1 benchmark:

• Graph Classification - Metrics: Accuracy, Accuracy (10 fold), Inference Time (ms)

Recent Benchmark Submissions

Research Papers

Recent papers with results on this dataset:

• FIT-GNN: Faster Inference Time for GNNs Using Coarsening (2024) -
• PANDA: Expanded Width-Aware Message Passing Beyond Rewiring (2024) -
• An end-to-end attention-based approach for learning on graphs (2024) -
• Fine-tuning Graph Neural Networks by Preserving Graph Generative Patterns (2023) -
• Graph-level Representation Learning with Joint-Embedding Predictive Architectures (2023) -
• Transitivity-Preserving Graph Representation Learning for Bridging Local Connectivity and Role-based Similarity (2023) -
• Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes (2023) -
• Randomized Schur Complement Views for Graph Contrastive Learning (2023) -
• CIN++: Enhancing Topological Message Passing (2023) -
• Strengthening structural baselines for graph classification using Local Topological Profile (2023) -
• Cell Attention Networks (2022) -
• TREE-G: Decision Trees Contesting Graph Neural Networks (2022) -
• 0/1 Deep Neural Networks via Block Coordinate Descent (2022) -
• DiffWire: Inductive Graph Rewiring via the Lovász Bound (2022) -
• Template based Graph Neural Network with Optimal Transport Distances (2022) -
• Recipe for a General, Powerful, Scalable Graph Transformer (2022) -
• DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (2021) -
• Maximum Entropy Weighted Independent Set Pooling for Graph Neural Networks (2021) -
• Fea2Fea: Exploring Structural Feature Correlations via Graph Neural Networks (2021) -
• How Attentive are Graph Attention Networks? (2021) -