## Implementing papers 👨🏻💻

This year my resolution is that I will implement 52 machine learning papers.

- 1. Graph Classification using Structural Attention
- 2. Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence
- 3. SINE: Scalable Incomplete Network Embedding
- 4. Watch Your Step: Learning Graph Embeddings Through Attention
- 5. Graph Wavelet Neural Network
- 6. Biological Network Comparison Using Graphlet Degree Distribution
- 7. Learning Role-based Graph Embeddings
- 8. SimGNN: A Neural Network Approach to Fast Graph Similarity Computation
- 9. Predict then Propagate: Graph Neural Networks meet Personalized PageRank
- 10. A Higher Order Graph Convolutional Network
- 11. Ego-splitting Framework: from Non-Overlapping to Overlapping Clusters
- 12. Splitter: Learning Node Representations that Capture Multiple Social Contexts
- 13. Capsule Graph Neural Network
- 14. GEMSEC: Graph Embedding With Self-Clustering
- 15. Jump Around! Multi-scale Attributed Node Embedding
- 16. Semi-Supervised Graph Classification: A Hierarchical Graph Perspective
- 17. MixHop: Higher-Order Graph Convolutional Architecturesvia Sparsified Neighborhood Mixing
- 18. GraRep: Learning Graph Representations with Global Structural Information
- 19. Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
- 20. EdMot: An Edge Enhancement Approach for Motif-aware Community Detection
- 21. Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation
- 22. A Non-negative Symmetric Encoder-Decoder Approach for Community Detection
- 23. Multi-scale Attributed Node Embedding
- 24. Overlapping Community Detection at Scale: A Nonnegative Matrix Factorization Approach

# Resolutions 2019

## A list of data mining and machine learning papers that I implemented in 2019.

### Resolutions 2019 Info

⭐ Stars19

🔗 Source Codegithub.com

🕒 Last Updatea year ago

🕒 Created4 years ago

🐞 Open Issues0

➗ Star-Issue RatioInfinity

😎 Authorbenedekrozemberczki