Implicit Differentiation

1 long-form post on Implicit Differentiation: machine-learning research by Taha Bouhsine, each built around live, in-browser interactive visualizations.

1 post tagged #implicit-differentiation.

Jul 1, 2026

A Network That Is a Fixed Point, in JAX/Flax NNX

A runnable companion: build the Yat deep-equilibrium network in JAX/Flax NNX. One shared operator F(z;x)=tanh(A·φ_W(z)+Ux+z0), solved to its fixed point by damped iteration, trained not by backprop-through-iterations but by implicit differentiation, the adjoint (I−Jᵀ)u=∂L/∂z* run by the same contraction. Plus the weight-tied maze operator that extrapolates from 11×11 to 27×27 by iterating longer. Every number is from a real run: 98.2% on two moons from 1700 shared parameters, ‖J‖ 0.66/0.92, 99.5% on mazes far larger than training.