graph-learning-papers-guide
Conference papers on graph neural networks and graph learning
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill graph-learning-papers-guide --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Graph Learning Papers Guide ## Overview A curated list of graph learning papers from top AI/ML conferences (NeurIPS, ICML, ICLR, KDD, WWW, AAAI). Covers graph neural networks, graph transformers, spectral methods, message passing, and applications in molecular science, social networks, and recommendation systems. Organized by venue, year, and topic for systematic tracking. ## Topic Taxonomy ``` Graph Learning ├── Graph Neural Networks │ ├── Message Passing (GCN, GAT, GraphSAGE, GIN) │ ├── Spectral (ChebNet, CayleyNet) │ ├── Graph Transformers (Graphormer, GPS) │ └── Equivariant GNNs (EGNN, SE(3)-Transformers) ├── Graph Generation │ ├── VAE-based (GraphVAE) │ ├── Autoregressive (GraphRNN) │ ├── Diffusion (GDSS, DiGress) │ └── Flow-based (GraphFlow) ├── Self-supervised Learning │ ├── Contrastive (GraphCL, GCA) │ ├── Generative (GraphMAE) │ └── Predictive (GPT-GNN) ├── Scalability │ ├── Sampling (GraphSAINT, ClusterGCN) │ ├── Knowledge distillation │ └── Graph condensation ├── Temporal Graphs │ ├── Dynamic GNNs │ ├── Temporal interaction │ └── Evolving graphs └── Applications ├── Molecular property prediction ├── Drug discovery ├── Social network analysis ├── Recommendation systems
- Overview
- Topic Taxonomy
- Key Models
- Paper Search
- Benchmark Datasets
- Use Cases
- References
What does the graph-learning-papers-guide skill do?
Conference papers on graph neural networks and graph learning
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill graph-learning-papers-guide --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.