NRI
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ethanfetaya
Neural relational inference for interacting systems - pytorch
Line 93 os.mkdir ----> os.makedirs Line 46 default='logs' ----> default='./logs' Not a big problem, Just mention it here for others' convenient.
Hi, I can not reproduce the experimental results of the charged simulation dataset. The accuracy is only 50+% and I didn't modify the code (just modify variable() to fit higher...
Below is the code snippet of MLPDecoder. I think prediction is ended with Eq. 11 in the paper. I can't find the code of Eq. 12. Am I missing something...
Hello, I have read the paper and the code and I'm fascinated about this tool and their possible applications. In my biological set-up I have different objects from which I...
There is no supervised training in training. How to know the first type is the existence side and the second type is the non existence side. `def edge_accuracy(preds, target): _,...
The step x = F.elu(self.fc1(inputs)) has error. When using the forward in MLP class, the error says "mat1 and mat2 shapes cannot be multiplied (640\*16 and 196\*512)".
Hello, thank you for your great work and nice code. I saw the [supplementary material](http://proceedings.mlr.press/v80/kipf18a/kipf18a.pdf), and it said that NRI can learn "known" 3 edge types (no-interaction, weak spring, strong...
For the system in which 2 particles interact or not, such as the spring experiments, if we use z_{ij}=[0,1] to denote interaction, and z_{ij} = [1,0] to denote non-interaction(no message...
Hi, Great paper. Do you plan to make your code compatible with Pytorch 1.xx ? Thanks.
Hi, thanks for the the code release. To make sure that I am running the code properly, I am trying to reproduce some of the paper results. What's the correspondence...
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Neural relational inference for interacting systems - pytorch