Open stochastic and probabilistic computing research, a learning portal for bitstream / p-bit hardware, and an interactive paper map of 105+ peer-reviewed works — bridging bitstream arithmetic, invertible logic, and energy-efficient inference hardware.

• Probabilistic Computing Leaßßrning Portal — Fundamentals → encoding & correlation → hardware taxonomies (newcomer-friendly; DOI citations only).
• Interactive PC Paper Map — Search, filter by research domain, and browse abstracts across 105+ curated stochastic / probabilistic computing papers with DOI links.
• Organization profile repo — Public catalog source (docs/papers.json), Pages site, and this landing page.

This organization profile repository provides:

• profile/README.md — this landing page (regenerated by scripts/export_papers_catalog.py).
• docs/index.html — Interactive Paper Map (GitHub Pages).
• docs/papers.json — Machine-readable catalog metadata (includes abstracts).
• .github/workflows/deploy-pages.yml — Pages deployment.

Learning curriculum lives in a public repo: public (site). It does not host paper PDFs or private lab materials.

Do not hand-edit profile/README.md or docs/papers.json. Refresh with: python3 scripts/export_papers_catalog.py

Catalog metadata and organization profile documentation are licensed under CC BY 4.0. Publisher metadata, DOIs, and paper citations remain under the copyright of their respective publishers (IEEE, ACM, etc.). This repository does not host copyright-restricted PDFs.