Fuzzy Logic Interpretation of Quadratic Networks

Understand

Over past several years, deep learning has achieved huge successes in various applications.

• However, such a data-driven approach is often criticized for lack of interpretability.
• Recently, we proposed artificial quadratic neural networks consisting of second-order neurons in potentially many layers.
• In each second-order neuron, a quadratic function is used in the place of the inner product in a traditional neuron, and then undergoes a nonlinear activation.