proof-writer

To write rigorous ML/AI proofs, provide an exact theorem statement and explicit assumptions to formalize your claim into a structured proof package with step-by-step justifications and a dependency map.

Yes, you can formalize proof sketches and fill in missing steps for theorems, lemmas, propositions, and corollaries by validating your notation and assumptions against standard mathematical frameworks.

The best way to prove a convergence theorem is to supply the exact claim and learning dynamics, which generates a complete proof draft or a corrected claim with stepwise justification and error checks.

Yes, formalizing ML/AI proofs requires exact claim normalization, explicit assumptions, and notation to identify gaps in reasoning and output verifiable mathematical arguments.

Your proof draft has reasoning gaps due to unnormalized claims or implicit assumptions, which this approach identifies by validating structure and applying error checks against standard mathematical frameworks.

You should provide an exact theorem statement and assumptions from your research notes to receive a formalized, verifiable proof draft or a corrected claim with structured justification.