Dicklesworthstone/model_guided_research
Systematic investigation of 11 exotic math frameworks (Lie groups, tropical algebra, p-adic numbers, etc.) applied to deep learning, with dual JAX and PyTorch implementations
Why it is useful
model_guided_research is a recent open-source project in Education. It is included because it has recent repository activity and can support mathematical learning, research, modelling, software development, or AI workflows.
Repository at a glance
- Owner: Dicklesworthstone
- Primary language: Python
- Latest update: 2026-07-17
- Stars / forks: 116 / 15
- License: NOASSERTION
- Links: No separate project site was listed.
Good starting points
- Read the project README and installation instructions.
- Try the smallest example before changing parameters or datasets.
- Check tests, issues, and release notes before relying on results in teaching or research.
- Cite the repository and its license when reusing code or figures.
README snapshot
From theoretical exploration to production implementation: A systematic investigation of exotic mathematical structures in deep learning - Project Overview - What this project is about - Dual Implementation Strategy - Research (JAX) + Production (PyTorch) - Quick Start - Get up and running - The 11 Mathematical Frameworks - Browse all implementations - Nanochat: Production Transformer - Unified GPT with all 11 approaches - [Experimental Matrix](#-experimental