convex-neural-network

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• martindoff / DC-Deep-Neural-Network

  Learn dynamical systems as a difference of convex functions (DC) using a feedforward Neural Network (NN) architecture with DC structure. The resulting model learns the dynamics f in DC form as follows: f= f1 -f2 where f1 and f2 are convex functions. The DC structure of the network allows to independently express f1 and f2 as two input convex NN.

  convexdc-decompositiondc-programdeep-learningdifference-of-convex-functionsfeedforward-neural-networkneural-networkconvex-neural-network
  Language:Python 0