Method for training a first neural network for each of a set of intra-prediction modes for block-based picture coding for determining an intra-prediction signal for a current block by applying a first set of neighboring samples of the current block onto the first neural network (80, 80 0 , 80 KB-1 ) for the respective intra-prediction mode, comprising applying, for each of the set of intra-prediction modes, a first set of neighboring samples neighboring a first picture test block onto the first neural network for the respective intra-prediction mode so as to obtain, for each of the set of intra-prediction modes, a prediction signal for the first test block, and a second set of neighboring samples neighboring the first picture test block onto a second neural network (84, 84 0 , 84 KB-1 ) so as to obtain, for each of the set of intra-prediction modes, a probability value indicative of a probability of the respective intra-prediction mode; determining , for each of the set of intra-prediction modes, a coding cost estimate for coding costs related to prediction error coding and mode signalization using the prediction signal obtained for the respective intra-prediction mode; updating first parameters of the first neural network for each of the set of intra-prediction modes and second parameters of the second neural network so as to reduce a coding cost function having (i) a first addend forming a residual rate estimate depending on the prediction signal obtained for an intra-prediction mode of the lowest coding cost estimate and (ii) a second addend forming a mode signaling side information rate estimate depending on the prediction signal and the probability value obtained for the intra-prediction mode of the lowest coding cost estimate; and sequentially repeating the applying, determining and updating for a plurality of picture tests blocks with using the first and second parameters as updated for one picture test block for the application of the next picture test block of the plurality of picture test blocks. applying, for each of the set of intra-prediction modes, a first set of neighboring samples neighboring a first picture test block onto the first neural network for the respective intra-prediction mode so as to obtain, for each of the set of intra-prediction modes, a prediction signal for the first test block, and a second set of neighboring samples neighboring the first picture test block onto a second neural network (84, 84 0 , 84 KB-1 ) so as to obtain, for each of the set of intra-prediction modes, a probability value indicative of a probability of the respective intra-prediction mode; determining , for each of the set of intra-prediction modes, a coding cost estimate for coding costs related to prediction error coding and mode signalization using the prediction signal obtained for the respective intra-prediction mode; updating first parameters of the first neural network for each of the set of intra-prediction modes and second parameters of the second neural network so as to reduce a coding cost function having (i) a first addend forming a residual rate estimate depending on the prediction signal obtained for an intra-prediction mode of the lowest coding cost estimate and (ii) a second addend forming a mode signaling side information rate estimate depending on the prediction signal and the probability value obtained for the intra-prediction mode of the lowest coding cost estimate; and sequentially repeating the applying, determining and updating for a plurality of picture tests blocks with using the first and second parameters as updated for one picture test block for the application of the next picture test block of the plurality of picture test blocks. <EOS>