Formal proofs of paper theorems#
The mononet repository contains a Lean 4 / mathlib4 formalization of every
theorem in the paper, living under proofs/.
This page is the cross-reference: paper claim ↔ Lean theorem ↔ Python
property test.
Trust model#
The formalization has one axiom: Theorem 4 of Daniels & Velikova
(2010, Monotone and Partially Monotone Neural Networks). Every other claim
is proved from first principles using mathlib4. See
proofs/Mononet/DanielsVelikova.lean
for the precise axiom statement.
A full port of Daniels & Velikova 2010’s proof is a deferred follow-up (tracked in the project’s GitHub issues).
Cross-reference table#
Paper claim |
Lean theorem |
Empirical counterpart |
|---|---|---|
Lemma 1 (sign of partial derivatives) |
|
|
Lemma 2 (combined activation mono + convex/concave) |
|
|
Corollary 3 (CMFCL properties) |
|
(covered by tests for Lemma 1 + Lemma 2) |
Lemma 5 (Heaviside approximation) |
|
|
Lemma 6 (affine rescale equivalence) |
|
|
Theorem 7 (universal approximation) |
|
|
Building the proofs locally#
cd proofs
lake exe cache get
lake build
Expected runtime: under 5 minutes if the mathlib4 cache is warm, ~15 minutes on a cold cache.
Doc-gen4 HTML#
The CI job uploads a doc-gen4-rendered HTML view of every module as a
workflow artifact named lean-docs. Download from any successful Lean
workflow run on the project’s Actions page. Hosting the rendered HTML at a
stable URL is a follow-up deliverable.