Hopefully it is easier to use than pytorch geometric

I actually find it (DGL) very easy to use. I switched from PyG just over a year ago because DGL was easier to install across MacOS, Linux, and Windows. Some of the recent PyG updates are interesting but not enough for me to move back. Anyway, I find both libraries to be very similar so I think either choice is good.

I was using it on my research, I’m glad the first stable version dropped. I’ll check the changes.

I have been struggling to get the accuracy with DGL above 60. So i stick with PyG.

Will test out a few GNNs on some random dataset to see if it works better now.

I'm using it on my masters thesis atm. Having problems because of a deprecated feature without replacement (g sampling)

Haha, I'm using PyG for my MASc thesis at the moment. Maybe scope it out a bit; the PyG slack channel is very active and super helpful.

Interesting as I have not had much trouble reproducing the results from papers I use as baselines. I find that sometimes, weight initialisation can make a difference so read the paper carefully on how they initialised the convolutional layer weights and check that DGL is using the same method. If not, do a custom initialisation based on the paper.