85 points by datawhiz123 10 months ago flag hide 13 comments
john_doe 10 months ago next
Fascinating topic! I've been exploring GNNs recently and it's amazing how concepts from graph theory are influencing this field.
jane_doe 10 months ago next
Totally agree, John! The interplay of graph theory and neural networks could open up new opportunities for solving complex problem.
graph_wiz 10 months ago prev next
Undirected, directed, acyclic and edge-weighted graphs all have relevant counterparts in the design of Graph Neural Networks!
john_doe 10 months ago next
Interesting insight! Would love to see some real-world applications using this idea.
code_diva 10 months ago next
Here's a great paper on applying GNNs to chemo-informatics datasets: [url](https://arxiv.org/abs/1703.06303). It discusses using graphs for molecular analysis.
ml_enthusiast 10 months ago prev next
Some researchers are already using GNNs to improve performance in prediction and recommendation systems. This is really exciting!
random_user 10 months ago next
@ML_enthusiast can you please link some of these research papers you have mentioned? It would be great to read them.
researchscout 10 months ago next
Check out this survey paper for a comprehensive overview of recent advancements in GNNs: [url](<https://arxiv.org/abs/1812.08434>). It contains a lot of valuable information on both fundamentals and applications.
jan_meyer 10 months ago prev next
This is similar to attention mechanism! Like when you apply graph Attention Networks for traffic prediction.
ml_enthusiast 10 months ago next
@jan_meyer Precisely, there's a lot of common ground between graph theory principles and modern AI techniques. It's opening up unique possibilities.
graphical_whiz 10 months ago prev next
People often skip over isomorphism concepts when discussing GNNs, but they're going to be more important the deeper you go into graph neural networks.
programmingprophet 10 months ago next
Graph isomorphism is indeed interesting when thinking about concepts like permutation equivariance. Excited to see new techniques.
fastforward 10 months ago prev next
Utilizing isomorphism property opens way to learn from examples rather than explicit graph manipulation. Anyone thinking about scaling GNNs should experiment with this.