GraphCL
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Shen-Lab
[NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen
### I have tried my dataset on your unsupervised learning framework, which num_of_edge will exceed 10^6. When I load the data, there is an assertion error. -------------------------------- loading GCC 7.3.1...
Question about data augmentation: When subgraph augmentation is performed, essentially only the enge_index is modified. This means that only the subgraph is aggregated for information propagation. What puzzles me is...
There is a package import _'from cortex_DIM.functions.gan_losses import get_positive_expectation, get_negative_expectation'_ Neither '_pip install cortex_DIM_' nor '_conda install cortex_DIM_' could work. I wander how can i add this cortex_DIM to my...
Hi, can you add information about the datasets? such as their names, their meanings, what they represent... I trying finding it in the article and didnt find anything. Specificaly information...
File "/home/test02/code/GraphCL-master/semisupervised_TU/pre-training/feature_expansion.py", line 27, in __init__ super(FeatureExpander, self).__init__('add', 'source_to_target') TypeError: __init__() takes from 1 to 2 positional arguments but 3 were given
How can I use GraphCL for fully unsupervised Graph Clustering? So far, all that I've found the method for Graph Clustering is actually for node clustering or not a fully...
Hi! In Unsupervised-TU, such as logistic regression classifier, there are two parts, test and val, annotated in the ten fold cross verification section. But in my opinion, these two parts...
Traceback (most recent call last): File "execute.py", line 222, in tot = tot.cuda() File "/HOME/scz1727/run/ENTER/envs/pytorchzq/lib/python3.8/site-packages/torch/cuda/__init__.py", line 216, in _lazy_init torch._C._cuda_init() RuntimeError: No CUDA GPUs are available 谢谢，期待您的解答。
main.py 320 run_exp_benchmark() main.py 278 run_exp_benchmark run_exp_lib(create_n_filter_triples(datasets, feat_strs, nets, main.py 183 run_exp_lib cross_validation_with_val_set( train_eval.py 115 cross_validation_with_val_set train_loss, _ = train( train_eval.py 234 train out1 = model.forward_cl(data1) res_gcn.py 173 forward_cl return...
