Resources
This page is a collection of useful resources, blogs, papers, and more that I’ve found for a variety of topics. Listing something here doesn’t mean I support everything the author says.
Really Cool Blogs:
- Gwern
- Evoiding
- Michael Nielsen
- Milan Cvitkovic ← Great post about agency
- Patrick Collison ← This advice page is particularly useful for high schoolers
- Jeff Kaufman
- Chris Olah
- The Batch from DeepLearning.AI ← I know this is technically a newsletter
- Lilian Weng
Some of my Favorite Papers:
- A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise
- You Only Look Once: Unified, Real-Time Object Detection
- Building Machines That Learn and Think Like People
- Grad-CAM
- CAM
- Neural Machine Translation by Jointly Learning to Align and Translate
- A Survey of Unsupervised Domain Adaptation for Visual Recognition
- Risks from Learned Optimization in Advanced Machine Learning Systems
- Attention Is All You Need
- Locating and Editing Factual Associations in GPT
- A Mathematical Framework for Transformer Circuits
- Thread: Circuits
- Understanding and Improving Layer Normalization
- Disentangling by Subspace Diffusion
- A Note on Random Projections for Preserving Paths on a Manifold
Quick-ish Reference Materials:
- My Git Guide
- Someone else’s Git Guide
- LaTeX Reference
- Jekyll Markdown Reference
- State of AI
- IMAGENET Classes
Good Technical Books:
Cool Ideas:
Other Fun Stuff 🙂: