Training step L0L1LT 1W Preprocessing f(x, v) T

In the following sections, we provide additional details about the network architecture, training, and experiments. The source code and WBC-SPH data set are published at https://github.com/ A.1 Implementation Details We implement our neural network with Tensorflow (https://www.tensorflow.org), They also serve as the basis for the implementation of our antisymmetric CConv (ASCC) layer. Axis for Mirroring As mentioned in the main text, the mirror axis for ASCC layers can be chosen freely while fulfilling the requirements from theory. This provides a degree of freedom for implementation. We decided to use a fixed axis, which in our case corresponds to the spatial y-axis. While the mirroring could potentially be coupled to the spatial content of features, we found that a single, fixed axis for mirroring simplifies the implementation of the ASCCs, and hence is preferable in practice. Additional Modifications In addition to the properties of our algorithm as discussed in Section 2.3 and the ablation study in Section 3, we normalize the input data depending on the given gravitational direction in the model.