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License: MIT License
DeepInf: Social Influence Prediction with Deep Learning
License: MIT License
the number of sub-network formed by active neighbors / the number of sub-network formed by neighbors ?
Hey! I was interested into why are you using tanh here:
attn_src = torch.matmul(F.tanh(h_prime), self.a_src) # bs x n_head x n x 1
in BatchMultiHeadGraphAttention, get_layers.py. Did it stabilize the training? Is it some form of feature normalization?
您好:
感谢您分享的代码,关于多头attention计算的部分有两处问题想请教,希望能得到您的回复:
1. Line84请问这一行的self.w是相当于paper中的参数c吗?
2. Line85,86,87中h_prime分别与self.a_src和self.a_dst相乘再相加,是对应paper中[Whj||Whi]的部分吗?
希望能得到您的回复,非常感谢!
祝好!
I have a question about the input data: I am wondering whether the last element of each row in the"vertex_id.npy" is the ID for ego node?
I am also curious whether you the data processing script is being released or not?
您好,请问您能提供数据集预处理的代码吗?我想尝试将您的方法运用在我自己的数据集上。感谢!
Hello, I am really interested in your research.
May I ask the parameters setting of your code, which can get the same best results in your paper 'DeepInf: Social Influence Prediction with Deep Learning'. Especially on your twitter dataset.
Many thanks.
Hello, I'm going to test your implementation using a custom dataset similar to Twitter. Do you have scripts to pre-process raw-data?
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