Heterogeneous Deep Graph Infomax

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Deep Learning Heterogeneous-Deep-Graph-Infomax
Overview

Heterogeneous-Deep-Graph-Infomax

Parameter Setting:

HDGI-A:

Node-level dimension: 16
Attention head: 4
Semantic-level attention vector: 8
learning rate: 0.02

HDGI-C:

Node-level dimension: 64
Semantic-level attention vector: 8
learning rate: 0.02

GAT:

Node-level dimension: 16
Attention head: 4
learning rate: 0.005
Drop out ratio: 0.6

GCN:

Hidden-unit dimension: 64
learning rate: 0.01
Drop out ratio: 0.5

RGCN:

Hidden-unit dimension: 16
learning rate: 0.01
Drop out ratio: 0

Metapath2Vec:

Embedding dimension: 100
learning rate: 0.01
negative-samples: 5
Window: 1

HAN:

Node-level dimension: 16
Attention head: 4
Semantic-level dimension: 8
learning rate: 0.005
Node-level Drop out ratio: 0.6
Semantic-level Drop out ratio: 0.6

Deepwalk:

Number of walks per node: 10
Dimensions of word embeddings: 128
Length of random walk: 30
Window size for skipgram: 5

DGI:

Hidden-unit dimension: 64
learning rate: 0.001
Drop out ratio: 0

Comments
  • about the experiment

    about the experiment

    Great respect for your work. I just have a question about the result of the HAN model. Did you just use the TensorFlow version of HAN implemented by the author? Because I can't reproduce the results he mentioned in his paper. So any suggestion?

    opened by DannyWu1996 11
  • out of memory

    out of memory

    Hi, I am excited to see this work. But when I trained the HDGI-HGAT model with GTX-1080ti GPU, I got the following error: RuntimeError: CUDA out of memory. Tried to allocate 146.88 MiB (GPU 0; 2.00 GiB total capacity; 374.63 MiB already allocated; 0 bytes free; 1015.00 KiB cached) Is there any solution? Looking forward to your reply.

    opened by 960924 3
  • Dropout and ratio

    Dropout and ratio

    Hi, thanks your job! When I m trying your code, I dont find anywhere using the dropout operation. So, why you set the drop_prob parameter? Meanwhile, in your paper, you conducted two different training-ratio(20% and 80%), and you show the case of 20%. So ,when it comes to 80%, how can i split the dataset? 10% for validation and 10% for test? i hope for your response! Thank U very much!

    opened by liun-online 2
  • Could you please release the code of DGI experiment with any dataset?

    Could you please release the code of DGI experiment with any dataset?

    As shown in experiment in the paper, DGI perfomance is strongly competitive. But I am very curious about its implementation, because DGI is applicable only on isomorphic graph, how could your team apply this method to a heterogeneous graph? Thanks so much if you do release the code. If not, could you please briefly describe the experiment?

    opened by Yonggie 1
  • IMDB extract Edge

    IMDB extract Edge

    opened by NlpRookie 1
  • The Question about the cluster experiment of HDCN

    The Question about the cluster experiment of HDCN

    Hello, Mr Ren, after reading your paper, as you described in the paper, the gcns performance is better than the gat, while in the code, i only discover the cluster code about the gat, in the DGI-HGCN, i cannot find the cluster experiment of this gcns framework, could it really improve the cluster performance? (owing to missing this part code, leading these two framework is not symmetric, no offense, i`m curious because im a rookie ,thanks!!!)

    opened by YcZ76 6
  • other experiments

    other experiments

    Great respect for your work. Have you conducted other experiments? I used TSNE for visualization and found that the results were not ideal. I don't know if this is normal. Looking forward to your answer. I hope I didn't disturb you.

    opened by xinchen1412 6
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