Side note: one project I would like to do myself is a followup to YY Ahn et al's Flavor Networks research, but this time with some extra.. `zest`: using the fl

Side note: one project I would like to do myself is a followup to YY Ahn et al's Flavor Networks research, but this time with some extra.. `zest`: using the flavor and ingredient networks, but turbocharging the model using some kind of molecular representation of the flavor compounds using e.g. dgl-lifesci for graph-based representations of individual molecules. Basically instead of food <-> ingredients <-> flavor molecules (strings) relations use food <-> ingredients <-> flavor molecule (graphs) since graph neural networks are all the rage these days. I already made a kind of graph neural network thingy that works similarly for the AICrowd Learning to Smell competition that was kind of similar :) https://www.aicrowd.com/challenges/learning-to-smell https://www.aicrowd.com/challenges/learning-to-smell