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Built on Solid Mathematical Foundations

ZeroProofML extends PyTorch with Signed Common Meadow semantics, based on the pioneering work of Bergstra and Tucker on meadow algebra. Singularities become first-class algebraic states tracked by ⊥ and sign operators. Train with smooth projective tuples ⟨N,D⟩ and ghost gradients, deploy with strict inference and configurable thresholds. Use it anywhere division by zero matters: robotics, physics simulations, spectral analysis, financial models, or scientific computing.