no code implementations • 6 May 2021 • Clemens Hutter, Recep Gül, Helmut Bölcskei
One of the most influential results in neural network theory is the universal approximation theorem [1, 2, 3] which states that continuous functions can be approximated to within arbitrary accuracy by single-hidden-layer feedforward neural networks.