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Currently the link-prediction split is done by randomly splitting all the edges. We need an option to hold out nodes and their links in test set for inductive setting.
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Original Author: @shelby3
Original URL: https://github.com/keean/zenscript/issues/35#issue-243345358
Original Date: July 17, 2017
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Hello, now if I have many graphs, how can train these data? It seems that the code can just train on one graph data.
secuy updated
11 months ago
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Is it possible for the model to give/predict embeddings for unseen entities or relations that are not there in the train, test and valid datasets.
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### Week 1 - Get to know the community
- [X] Join the communication channels
- [X] Open a GitHub issue (this one!)
- [X] Install the Ersilia Model Hub and test the simplest model
- [X] Write a motiva…
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**Describe the bug**
The function just does not work. When I try to use it, I get:
AttributeError: module 'scholarly' has no attribute 'get_pubs'
**To Reproduce**
import scholarly
results = s…
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### Week 1 - Get to know the community
- [X] Join the communication channels
- [X] Open a GitHub issue (this one!)
- [x] Install the Ersilia Model Hub and test the simplest model
- [x] Write a motiva…
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你好,对你们的对接程序很感兴趣,谢谢你发展了KarmaDock。看你们昨天发布的文章。比较好奇为什么你们不用equibind提供的time split划分做下模型训练来进行公平的比较呢?我清楚time split划分没意义,但是文章里提到不公平比较然后使用tankbind这一点似乎有点牵强了吧。是比不过他们,所以没放数据吗?你们的思路我以前实现过,就是用DeepDock那套打分以及构象优化(构象优…
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# What is a grah neural network?
A graph neural network is a class of neural networks that takes a graph (nodes and edges), feature vectors representing nodes and edges as input and and uses layers…