JsonGrinder.jl: automated differentiable neural architecture for embedding arbitrary JSON data

Šimon Mandlík, Matěj Račinský, Viliam Lisý, Tomáš Pevný

Paper URL: https://jmlr.org/papers/v23/21-0174.html

Paper Availability And License: Yes

Code Of Conduct: Yes

TLDR: We present a library adding support to train a discriminative neural networks on the data stored in hierarchical formats like XML, JSON, ProtoBuffer, MessagePack, etc.

Submission Number: 6