Columbia U’s Infinitely Deep Probabilistic Model Adapts Its Complexity to the Data at Hand
While today’s deep neural networks (DNNs) are driving AI’s deep-learning revolution, determining a DNN’s appropriate complexity remains challenging. If aContinue Reading