In this section, we will cover a few recent and yet-to-be-explored topics of GANs that are challenging, interesting, and valuable.
In my opinion, one of the most interesting topics in GANs and deep learning is verified AI. This topic was described in Sanjit Seshia's Towards Verified AI paper in 2016 and is later addressed in a blog post by Google's DeepMind team. There are many challenges involved in achieving verified AI. Some of these challenges include testing, training, and formally proving that the models are specification-consistent.
Other fields that have recently received attention from GAN researchers include biology and its related subfields. There are GAN models that address the problem of drug discovery (3D Molecular Representations Based on the Wave Transform for Convolutional Neural Networks) and real-valued time...
