labmlai/annotated_deep_learning_paper_implementations
🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠
Build with Backblaze B2
SDKs, agent skills, IDE extensions, and reference pipelines from Backblaze Labs. All open source.
Loading star history...
Where it stands
Rank, growth pace and release cadence relative to everything GStars tracks.
The project lists 40 contributors on GitHub.
Gained 46% fewer stars in the last 90 days than in the 90 days before.
Use Cases & Benefits
- Provides over 60 PyTorch implementations of deep learning papers with side-by-side explanatory notes for better understanding.
- Combines code and detailed documentation to facilitate learning and experimentation with state-of-the-art neural network architectures and algorithms.
- Use for studying and reproducing transformer models including GPT, Vision Transformer, and Switch Transformer with clear tutorials.
- Use for exploring generative models like GANs, diffusion models, and reinforcement learning algorithms with practical implementations.
- Use for experimenting with advanced optimizers, normalization techniques, and adaptive computation methods in deep learning research.
Should you depend on it?
License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.
License
MIT
Permissive: commercial use, modification and redistribution are allowed with attribution.
Community files
- README: present
Watch-outs
- No GitHub releases; pin a commit or tag instead of a release.
General guidance from repository metadata, not legal advice. How we score
From the README
This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations,
The website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better.
We are actively maintaining this repo and adding new implementations almost weekly. for updates.
Daily snapshots
Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots
+371 stars over 78 days across 7 snapshot days; best day +9 on Nov 5.
Forks
6.8K+38
Open issues
46+13
Compared with peers in Deep Learning
Fastest-growing repositories GStars tracks in this cohort for the week of Nov 8, by 7-day star growth
| Repository | Stars | +7d | Health | Last release |
|---|---|---|---|---|
| rohitg00/ai-engineering-from-scratch | 78.3K | +1.6K | 75 | 1 day ago |
| labmlai/annotated_deep_learning_paper_implementations | 67.7K | — | 30 | — |
| SYSTRAN/faster-whisper | 26.5K | — | 40 | 368 days ago |
| GeeeekExplorer/nano-vllm | 16.3K | — | 12 | — |
| Lightning-AI/litgpt | 13.8K | — | 58 | 129 days ago |
| data-privacy-stack/presidio | 11.8K | — | 64 | 10 days ago |
| Category median | 16.3K | — | 58 | — |
Discover Repositories
Search across tracked repositories by name or description