In table Q&A tasks people are using stuff like BERT to represent a table (where data can be non-sequential, aka you can rearrange table columns and still have the same info).

They do that to represent a structured table as an unstructured text and perform question answering over it using the table as the context. But to be frank, it is not fully non-sequential data representation as the user's question in the end is a text, which is a sequential data source.

I do not know for sure, but I suspect the author is using GANs (Generative Adversarial Networks) to do this. There are many GAN versions that create drawings and sketches from images. Here are some references:

• RPD-GAN: Learning to Draw Realistic Paintings with Generative Adversarial Network
• I used a similar approach to generate a sketch of my photo too. large-scale image datasets with learning analytics

I used a similar approach to generate sketch of my photo too. Here it is.