Machine learning discovers invariants of braids and flat braids
Alexei Lisitsa Mateo Salles Alexei Vernitski
We use machine learning to classify examples of braids (or flat braids) as
trivial or non-trivial. Our ML takes form of supervised learning using neural
networks (multilayer perceptrons). When they achieve good results in
classification, we are able to interpret their structure as mathematical
conjectures and then prove these conjectures as theorems. As a result, we find
new convenient invariants of braids, including a complete invariant of flat
braids.