2019
Discrete Object Generation with Reversible Inductive Construction
NeurIPS 2019poster
The success of generative modeling in continuous domains has led to a surge of interest in generating discrete data such as molecules, source code, and graphs. However, construction histories for these discrete objects are typically not unique and so generative models must reason about intractably l…