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📚 Paper Implementations Collection

A curated collection of cutting-edge research papers brought to life through code implementations

Welcome to my comprehensive repository of research paper implementations! 🚀 This collection showcases my journey through the fascinating world of AI, Machine Learning, and Financial Technology research. Each implementation represents a deep dive into groundbreaking papers, transforming theoretical concepts into practical, runnable code.

🎯 About This Repository

As an AI Engineer and PhD student specializing in artificial intelligence with a passion for finance, I believe that understanding comes through implementation. This repository serves as:

  • 🔬 Research Laboratory: Hands-on exploration of state-of-the-art papers
  • 💡 Learning Resource: Detailed implementations with explanations
  • 🌉 Theory-to-Practice Bridge: Converting research insights into actionable code
  • 📖 Knowledge Sharing: Open-source contributions for the AI community

🗂️ Research Categories

🧠 Large Language Models & Reasoning

Exploring the frontiers of language understanding and reasoning capabilities

Paper Title Repository Status Key Techniques
Monte Carlo Tree Search Boosts Reasoning via Iterative Preference Learning 📁 MCTS Preference Learning ✅ Complete MCTS, DPO, Qwen-1.5B
Enhancing Reasoning through Process Supervision with Monte Carlo Tree Search 📁 MCTS Process Supervision ✅ Complete MCTS, Process Supervision, Qwen3

📊 Financial AI & Trading

Advanced methodologies for financial modeling and trading strategies

Paper Title Repository Status Key Techniques
Multi-dimensional queue-reactive model and signal-driven models: a unified framework 📁 Unified LOB Framework ✅ Complete Markov Generators, MLE, Lyapunov Analysis
To Hedge or Not to Hedge: Optimal Strategies for Stochastic Trade Flow Management 📁 Trade Flow Management ✅ Complete Riccati Solver, PDE Methods, RL
Regime-Switching Heston-Hull-White Model 📁 Regime-Switching Heston-Hull-White ✅ Complete Stochastic Calculus, Regime Switching
Neural Options Pricing 📁 Neural Options Pricing ✅ Complete Neural SDEs, Wasserstein Distance, Risk-Neutral Pricing

📝 Note: This repository is actively growing! New paper implementations are being added regularly. Check back often for updates or star the repository to stay notified.

📋 Implementation Standards

Each implementation follows a consistent structure to ensure quality and reproducibility:

🔧 Repository Structure

paper-name-implementation/
├── 📄 README.md              # Paper summary & implementation details
├── 📊 requirements.txt       # Dependencies
├── 🐍 src/                   # Source code
├── 📓 notebooks/             # Jupyter notebooks with experiments
├── 📈 results/               # Outputs, figures, and metrics
├── 🧪 tests/                 # Unit tests
└── 📚 docs/                  # Additional documentation

📝 Entry Format Template

| [Paper Title](paper-arxiv-link) | [📁 Repo](https://github.com/artaasd95/repo-name) | ✅ Complete | Technique1, Technique2 |

🏷️ Status Legend

  • Complete: Fully implemented and tested
  • 🔄 In Progress: Currently under development
  • 📋 Planned: Scheduled for implementation
  • 🔍 Under Review: Code review and optimization phase

🚀 Quick Start

  1. Choose a paper from the categories above
  2. Click the repository link to access the implementation
  3. Follow the README in each repository for setup instructions
  4. Run the experiments and explore the results!

🤝 Contributing & Collaboration

I welcome discussions, suggestions, and collaborations! Feel free to:

  • 🐛 Report Issues: Found a bug? Let me know!
  • 💡 Suggest Papers: Have a paper you'd like to see implemented?
  • 🔀 Contribute: Improvements and optimizations are always welcome
  • 💬 Discuss: Reach out for research collaborations

📫 Connect With Me

📊 Repository Stats

GitHub stars GitHub forks Last Commit


🎯 Research Philosophy

"The best way to understand a breakthrough is to rebuild it from scratch."

Each implementation in this collection represents not just code, but a journey of understanding—from the first read of the paper to the final working system. Through this process, we uncover the nuances, challenges, and insights that only come from hands-on experience.


Star this repository if you find it helpful, and watch for updates as new implementations are added regularly!

Happy Learning & Building! 🚀

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List of implementation (reproduce) of academic paper for educational purposes

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