The Square ReLU Activation Function
Neural Units & Activations DS practice problem on Onlearn.
Difficulty: easy.
Topics: Understanding Non-Linear Activation Functions in Deep Learning, Rectified Linear Unit (ReLU) variants, Element-wise squashing functions, Thresholding operations, Differentiability at the origin, Mathematical mapping of input spaces, Deep Learning, Calculus, Optimization, Function Approximation, Computational Mathematics, Activation Functions, Non-linearity, Gradient Flow, Neural Network Architectures, Vectorized Operations.
Implement the Square ReLU activation function. The Square ReLU is defined as f(x) = x^2 if x 0, and f(x) = 0 if x <= 0. Your function should accept a single numerical input or a list of numbers and return the transformed value(s).