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## Title & Topic
- sequence prediction 분야에서의 transduction, transductive learning 개념과 방법론을 알아본다
- transducer로서의 RNN 개념을 파악한다
- transduction에서 파생된 트랜스포머 네트워크 개념을 이해한다
## Upload schedule
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Hi, @rusty1s , thanks for your really great job and wonderful codes!!! I am recently doing some jobs about Graph Representation Learning and I am working on Reddit dataset. It seems you deal with the …
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It would be nice to have a framework similar to `GridSearchCV` and `RandomSearchCV` for assessing unsupervised clusterers. Given a scoring function (silhouette score, or any other domain-appropriate w…
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您的代码attack-3中
logits_a = net2(generated_g, generated_features)
acc2 = evaluate(net2, sub_g_b, sub_features_b, sub_labels_b, sub_test_mask_b)
训练和测试的时候不是同一个graph。但是GCN不是一个transductive learning吗?为什么…
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Hello,
I'm hoping to confirm that the hyperparameters specified in your paper are correct. Specifically, for miniimagenet, 100k meta steps were taken during training? I ask because it seems some of…
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Can this code (pygcn) be used directly in transductive learning? I notice that the train loss (in train.py) is calculated as `loss_train = F.nll_loss(output[idx_train], labels[idx_train])`, but in pap…
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I am wondering if it makes sense to use GraphSAGE on graphs with no features? Does it still have an advantage over DeepWalk? Why is GraphSAGE without features experiment is missing in the paper?
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Hi, Diego! Thank you for sharing the code.
I have read and run the code in branch **similar_impl_tensorflow**. There are some questions I confuse about.
The paper of GAT tells that the author re…
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You separate the images in each class into disjoint labeled and unlabeled sets. Why we can't sample labeled images and take the remained images as unlabeled split and sample unlabeled data from here? …