  In order to continuously represent molecules, we propose a generative model
in the form of a VAE which is operating on the 2D-graph structure of molecules.
A side predictor is employed to prune the latent space and help the decoder in
generating meaningful adjacency tensor of molecules. Other than the potential
applicability in drug design and property prediction, we show the superior
performance of this technique in comparison to other similar methods based on
the SMILES representation of the molecules with RNN based encoder and decoder.
