pngwn/linearizer-minimal-repro

Minimal Repro: "Who Said Neural Networks Aren't Linear?" (the Linearizer, arXiv:2510.08570) A ~250-line 2D toy that proves the paper's core principle end to end. Not a full-paper reproduction (no LPIPS, no image diffusion, no large-scale training) — just the smallest experiment that demonstrates: Induced linearity is exact. f(x) = g⁻¹(A·g(x)) satisfies f(a·x+b) = a·f(x) + b·f(0) to machine precision when the identity is evaluated in the space where the algebra happens (g-space)… See the full description on the dataset page: https://huggingface.co/datasets/pngwn/linearizer-minimal-repro.