I have a distribution built on an interval for example
[v_min, v_max], given a good estimate on the interval, the performance of the model can be good. If the interval is not the right interval, it will impede the performance of the model. Now I want to design such a deep learning model so that the neural network can learning a good interval. Since the network is quite different. The output is bounded and it has constraint
v_min < v_max.
How can I design such a network?