All these functions E, D, and f R can be realized as neural networks. Once the models are trained (see Section Training), we can apply the auto differentiation techniques to the neural network f R in order to do search in the molecule embedding space R n . The minimization of L v0 will consist in fixing the weights of neural network and varying the argument Z in the direction of the gradient of L v0 (Z) in R n . Once the gradient descent converged to some vector Z 0 in R n such that f R (Z 0 ) is close enough to v 0 , we can reconstruct a molecule D(Z 0 ) by applying the decoder mapping D (Fig. ).