The optimization framework is agnostic to the architecture of the encoder and the decoder. Nevertheless, the properties of the latent space will greatly impact the optimization performance. In particular, the existence of "holes" in latent space or regions of the space with invalid molecules, will impact the ability of the agent to interpolate into the space. An additional parameter is the continuity or smoothness of the latent space which will facilitate optimization of molecules through a local search. Finally, the "coherence" between the encoder and decoder, that is the generation of molecules conditionally on the latent representation as opposed to random sampling, can greatly impact the ability to control the generation of molecules with desired properties. Certain encoder-decoder architectures are known to suffer from a phenomenon known as posterior collapse which results in a decoder that generates molecules independently of the latent variable .