Machine Learning, Neural Network Algorithm, Differential Equations.
weights and biases which depend on time, the transformation in the ODENet is defined for all t, giving us a continuous expression for the derivative of the function we are approximating. Another difference is that, because of shared weights, there are fewer parameters in an ODENet than in an