https://github.com/geraked/complex-networks
Implementation of Complex Networks Algorithms
https://github.com/geraked/complex-networks
amirkabir-university community-detection complex-network complex-networks complex-networks-from-scratch complex-neural-networks cs224w geraked gnn graph-algorithms graph-neural-networks heterogeneous-graph-neural-network influence-maximization outbreak-detection rabist spectral-clustering
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Implementation of Complex Networks Algorithms
- Host: GitHub
- URL: https://github.com/geraked/complex-networks
- Owner: geraked
- License: mit
- Created: 2023-04-26T02:53:33.000Z (about 2 years ago)
- Default Branch: master
- Last Pushed: 2023-04-26T02:57:05.000Z (about 2 years ago)
- Last Synced: 2025-01-03T14:50:31.613Z (5 months ago)
- Topics: amirkabir-university, community-detection, complex-network, complex-networks, complex-networks-from-scratch, complex-neural-networks, cs224w, geraked, gnn, graph-algorithms, graph-neural-networks, heterogeneous-graph-neural-network, influence-maximization, outbreak-detection, rabist, spectral-clustering
- Language: Jupyter Notebook
- Homepage:
- Size: 10.6 MB
- Stars: 1
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Complex Networks Analysis
Implementation of Some of the Complex Networks Algorithms From Scratch in Python
## Homework 1
[Problems](hw1/problem.pdf) | [Solutions (Report)](hw1/report.pdf)
- Erdos-Renyi Random Graph, Small-World Model (Watts-Strogatz), Degree Distribution, Clustering Coefficient, Comparison with Real-world data ([Source code](hw1/src/q1.ipynb))
- Structural (Percolation) Phase Transition, Largest Connected Component, Giant Component ([Source code](hw1/src/q2.ipynb))
- Influence Maximization through Greedy and CELF Algorithms, Independent Cascade Model ([Source code](hw1/src/q4.ipynb))
- Outbreak Detection through Greedy and CELF Algorithms ([Source code](hw1/src/q5.ipynb))
## Homework 2
[Problems](hw2/problem.pdf) | [Solutions (Report)](hw2/report.pdf)
- Implementing and Comparing the Centrality Metrics (Closeness, Efficiency, Degree, Katz) ([Source code](hw2/src/q2/q2.ipynb))
- Spectral Clustering (Partitioning) Algorithm, Modularity and Min-cut Metrics ([Source code](hw2/src/q3/q3.ipynb))
- Community Detection Using Fast Modularity Optimization Algorithm ([Source code](hw2/src/q4/q4.ipynb))
## Final Project
[Problems](final-project/problem.pdf) | [Solutions (Report)](final-project/report.pdf)
- DBLP Node Classification, Heterogeneous Graph Neural Network (HGNN), Graph Convolutional Network (GCN), Graph Attention Network (GAT) ([Source code](final-project/src/q1.ipynb))
- Simplifying Graph Convolutional Networks (SGC), PyTorch Geometric (PyG), GNNs ([Source code](final-project/src/q2.ipynb))
## Author
**Rabist** - view on [LinkedIn](https://www.linkedin.com/in/rabist)
## Details
- **Course:** Complex Networks Analysis - MS
- **Teacher:** [Dr. Mostafa HaghirChehreghani](https://aut.ac.ir/cv/2350/Mostafa%20HaghirChehreghani?slc_lang=en)
- **Univ:** Amirkabir University of Technology
- **Semester:** Fall 2022
## License
Licensed under [MIT](LICENSE).