vgraphrnn / vgrnn Goto Github PK

In both training examples clip_grad_norm() is called after opt.step() so it isn't doing anything. It should either be removed or moved before the optimizer updates the model components

Hi there,

I have some questions about the code. First is where is SIVGRNN? The second one is what is the difference between 'vgrnn_detection' and 'vgrnn_prediction'？

Thanks for your reply!

Hi,

I'm trying to run your code but always fail to load the data at this line. Please find below the error log:

UnicodeDecodeError: 'ascii' codec can't decode byte 0x96 in position 8: ordinal not in range(128)

Thanks for your help!

Hello,

I am looking at the VGRNN_prediction.py script and I found what seems to be a bug on this line:

nll_loss += self._nll_bernoulli(dec_t_sl, adj_orig_dense_list[t])

Shouldn't it be:

nll_loss += self._nll_bernoulli(dec_t_sl, adj_orig_dense_list[t + 1])

in order to do link prediction for the graph at time T+1?
Did I misunderstand something?

Thanks

Hi,

I've been reading your paper and I wanted to play a bit with the datasets that you used for the experiments. I see that you have uploaded the pre-processed data for Facebook, Enron, and Colab, but I couldn't find the other three datasets.
Do you have the code to produce the time series for HEP-TH, Cora, and Social Evolution? Or even the pre-processed data like for the other datasets would be good.

Thanks,
Daniele