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https://github.com/ramsyana/math-papers-with-code

A collection of implementations of mathematical algorithms and concepts from various academic papers in multiple programming languages.
https://github.com/ramsyana/math-papers-with-code

academic-project c math paper python zig

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A collection of implementations of mathematical algorithms and concepts from various academic papers in multiple programming languages.

Host: GitHub
URL: https://github.com/ramsyana/math-papers-with-code
Owner: ramsyana
License: mit
Created: 2024-12-26T05:52:59.000Z (about 2 months ago)
Default Branch: main
Last Pushed: 2025-01-06T02:28:13.000Z (about 2 months ago)
Last Synced: 2025-01-06T03:24:23.216Z (about 2 months ago)
Topics: academic-project, c, math, paper, python, zig
Language: Python
Homepage:
Size: 85 KB
Stars: 1
Watchers: 1
Forks: 0
Open Issues: 0
Metadata Files:
- Readme: readme.md
- License: LICENSE

Awesome Lists containing this project

README

# Math Papers with Code

A collection of implementations of mathematical algorithms and concepts from various academic papers in multiple programming languages.

## Implemented Papers

### Current Implementations

| Paper Title | Author(s) | arXiv | Implementations | Status | Directory |
|------------|-----------|--------|-----------------|---------|-----------|
| Relative Sizes of Iterated Sumsets | Noah Kravitz | [2412.18598](https://arxiv.org/pdf/2412.18598) | ![Python](https://img.shields.io/badge/Python-3776AB?style=flat&logo=python&logoColor=white) | ✅ Complete | `papers/iterated-sumsets/` |
| The Neveu-Schwarz Group and Schwarz's Extended Super Mumford Form | Katherine A. Maxwell & Alexander A. Voronov | [2412.18585](https://arxiv.org/pdf/2412.18585) | ![Python](https://img.shields.io/badge/Python-3776AB?style=flat&logo=python&logoColor=white) | 🚧 In Progress | `papers/super-mumford/` |

### Implementation Status Legend

| Status | Description |
|--------|-------------|
| ✅ Complete | Implementation finished and tested |
| 🚧 In Progress | Currently being implemented |
| 📝 Planned | On roadmap for implementation |
| ⏸️ On Hold | Implementation paused |

### Coming Soon

Future papers will be added to this collection. Suggestions for new implementations are welcome through issues or pull requests.

## Repository Structure

Each paper implementation is organized in its own directory with its implementation:

```
.
├── README.md
├── papers/
│ ├── iterated-sumsets/
│ │ ├── README.md
│ │ └── python/
│ │ ├── iterated_sumsets.py
│ │ └── tests/
│ ├── super-mumford/
│ │ ├── README.md
│ │ └── python/
│ │ ├── core/
│ │ │ ├── __init__.py
│ │ │ ├── laurent_series.py
│ │ │ ├── matrix_ops.py
│ │ │ └── vector_spaces.py
│ │ ├── geometry/
│ │ │ ├── __init__.py
│ │ │ ├── grassmannian.py
│ │ │ └── line_bundles.py
│ │ ├── groups/
│ │ │ ├── __init__.py
│ │ │ ├── heisenberg.py
│ │ │ ├── neveu_schwarz.py
│ │ │ └── witt.py
│ │ ├── tests/
│ │ │ ├── __init__.py
│ │ │ ├── test_laurent_series.py
│ │ │ ├── test_matrix_ops.py
│ │ │ └── test_vector_spaces.py
│ │ ├── utils/
│ │ │ ├── __init__.py
│ │ │ └── validation.py
│ │ ├── README.md
│ │ └── pyproject.toml
│ └── future-papers/
│ ├── README.md
│ └── python/
└── common/
├── testing/
└── benchmarks/
```

## Using the Implementations

Each paper implementation includes its own README with specific instructions. For Python implementations:

```bash
# Example for Super Mumford project
cd papers/super-mumford/python
pip install -r requirements.txt
python -m pytest tests/
```

## Contributing

Contributions are welcome! To contribute:

1. Select a mathematics paper to implement
2. Create a new directory under `papers/`
3. Implement the paper's concepts
4. Include:
- README.md with paper details
- Source code
- Tests (if applicable)
- Docker support (if applicable)
- Documentation (if applicable)
- Performance benchmarks (optional)

Please see CONTRIBUTING.md for detailed guidelines.

## Paper Implementation Guidelines

Each paper implementation should:

1. **Documentation**
- Include link to original paper
- Explain key concepts
- Provide usage examples
- Document any assumptions or limitations

2. **Code Structure**
- Clear organization
- Well-commented code
- Tests
- Docker support (where applicable)

3. **Performance**
- Efficient implementations
- Benchmarking (optional)
- Optimization notes

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Acknowledgments

- All original paper authors
- Contributors to the implementations
- Open source community