MathPhysCS CodeLab
A dynamic index of my CodeLab experiments created while delving into core and frontier topics in mathematics of computation and mathematics of machine learning. Each entry links to a self-contained, reproducible notebook, where I primarily use Haskell alongside other practical category theory-focused programming languages (e.g., Idris, Agda, OCaml). These notebooks integrate theoretical exposition with runnable code, demonstrating a complete workflow from theory to practice: theory \(\rightarrow\) derivation \(\rightarrow\) code implementation & visualization. All notebooks are live-rendered with Quarto, version-controlled on GitHub, and additionally compiled to PDF for offline reading.
- Open Notebooks: Click any row in the table below to open the live notebook (supports R / Python / Julia / Haskell).
- Online Execution: Launch the entire CodeLab environment via Binder (no local setup required):
Note: Binder may take 1-2 minutes to load the environment. - Offline Access: PDFs of all notebooks are auto-built on Overleaf and synced to GitHub after every update—ensure full reproducibility and offline reading.
Table Columns:
- Notebook Title: Name of the experiment (links to live notebook).
- Last Updated: Timestamp of the latest revision (prioritize recent content).
- Author: Contributor(s) to the notebook (for collaboration tracking).