Noisy Gaussian NN – Robustness to Label Noise

This project explores how a simple 1-hidden-layer neural network handles increasing label noise when fitting a Gaussian curve.
We test three noise levels (σ = 0.05, 0.1, 0.2) to see when the network smooths effectively and when it starts to underfit.