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I'm very interested in your paper “Towards Expansive and Adaptive Hard Negative Mining: Graph Contrastive Learning via Subspace Preserving”. Can you provide the corresponding code? Thank you very much…
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Hi, thank you for your awesome work, the experiment results of the code are quite consistent with the paper.
I have some question about the role of contrastive learning in SGL, I notice that in the t…
zwb29 updated
2 years ago
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Hi, I am currently using your source code on the node classification task as a baseline for testing. However, I noticed that when I ran the code on the provided datasets without any modification, the …
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SUGRL has shown impressive performance and speed. However, the paper Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning found that the representation space p…
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**Original article:** T. Chen, S. Kornblith, M. Norouzi, and G. Hinton. “A simple framework for contrastive learning of visual repre-
sentations.” In: International conference on machine learning. PM…
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Thank you for contributing a great work. However, I noticed that you only calculated the accuracy on the 62 shortest UCR datasets. Do you have the results for the accuracy on the full UCR dataset? Als…
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Hi, thank you very much for sharing the codes of the paper. Integrating contrastive learning into skill discovery is very attractive.
However, I found that in this implementation, the state encoder…
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If we adopt the mixup strategy during training, how to samples x_i and x_j from the same class are considered as a positive pair ? Maybe we should sample two identical numbers form beta distribution …
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## 0. Paper
- paper: [link](https://aclanthology.org/2023.acl-long.677/)
- my slide (in Japanese): [link](https://speakerdeck.com/a1da4/wen-xian-shao-jie-whitenedcse-whitening-based-contrastive-…
a1da4 updated
4 months ago
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Hi everyone. I met the error saying
"RuntimeError: Expected to have finished reduction in the prior iteration before starting a new one. This error indicates that your module has parameters that wer…