You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
A mechanistic interpretability framework visualizing the Universal Approximation Theorem. It deconstructs Neural Networks into weighted ReLU basis functions to reveal how models construct complex non-linear topologies from piecewise linear segments.
🔍 Explore how Multi-Layer Perceptrons work by visualizing function approximation through Neural Basis Decomposition and Mechanistic Interpretability techniques.