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martindoff / DC-Deep-Neural-Network

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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.

deep-learning neural-network feedforward-neural-network convex difference-of-convex-functions dc-program dc-decomposition convex-neural-network
  • Updated Oct 21, 2023
  • Python

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