Redes neuronales guiadas con variables internas físicas: cuando la física guía a los datos en el Aprendizaje Profundo.

Abstract

  We present a hybrid methodology that combines neural network learning power and the physics incorporation on certain internal layers of the network. The tool has predictive and explanatory capacity, it outperforms classic networks in speed, data needs, filtering capacity and extrapolation power.