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ngrislain

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  1. Vibe Under Constraint - Claude Code writing Lean 4 (ngrislain.github.io)
    3 points 1
  2. Mamba-3 and the State Space Model Renaissance (ngrislain.github.io)
    1 points 0
  3. The Signature Method in Machine Learning (an interactive reading note) (ngrislain.github.io)
    1 points 0
  4. Zero-Cost POSIX Compliance: Encoding the Socket State Machine in Lean's Types (ngrislain.github.io)
    34 points 9
  5. Reading Note: Sequential-Parallel Duality in Prefix Scannable Models (ngrislain.github.io)
    2 points 0
  6. Show HN: Lean-pq a typesafe PostgreSQL connector for lean (github.com)

    I’ve been building lean-pq, a PostgreSQL connector for Lean 4. While Lean is primarily known for theorem proving, I believe its dependent-types and formal verification features make it the ideal target for AI Agents to…

    2 points 1
  7. Don't Vibe – Prove (ngrislain.github.io)
    4 points 1
  8. Lean-PQ – Type-safe PostgreSQL bindings for Lean 4 via libpq FFI (github.com)
    1 points 0
  9. How to Die Optimally – A Theory of Consumption When AI Takes Your Job (ngrislain.github.io)
    2 points 0
  10. Lean Advent of Code 2025 (github.com)
    1 points 2
  11. Teaching 3D Geometry with Pyxel (ngrislain.github.io)
    1 points 0
  12. Mathematical Beauty, Truth and Proof in the Age of AI (quantamagazine.org)
    2 points 0
  13. Post-Labor Economics Lecture 01 [video] (youtube.com)
    2 points 0
  14. A Practical Method for Testing Differential Privacy – By Andi Cuko (medium.com)
    1 points 0
  15. Show HN: Value likelihoods for OpenAI structured output (arena-ai.github.io)
    114 points 42
  16. RAG with Differential Privacy (arxiv.org)
    2 points 0
  17. DP-RAG (medium.com)
    2 points 0
  18. Show HN: A simple implementation of Differentially Private RAG (github.com)
    2 points 0
  19. Nostr – Wikipédia (fr.wikipedia.org)
    2 points 2
  20. Enhancing May App Service Quality While Safeguarding Patients' Data (sarus.tech)
    2 points 0
  21. Qrlew SQL Framework (qrlew.github.io)
    1 points 0
  22. Lake Nyos Disaster (en.wikipedia.org)
    2 points 1
  23. 1 points 0
  24. Anonymization: The imperfect science of using data while preserving privacy (science.org)
    3 points 1
  25. Discovering New Knowledge While Protecting Privacy (sarus.tech)
    1 points 0