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[Graph backdoor](https://www.usenix.org/conference/usenixsecurity21/presentation/xi)
```bib
@inproceedings{xi2021graph,
title={Graph backdoor},
author={Xi, Zhaohan and Pang, Ren and Ji, Shouli…
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**Is your feature request related to a problem? Please describe.**
Deep Learning models usually are stacked layers, from shallow layers to deep layers. With Transform models being prevalent, it is wo…
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### Title
Hypergraph Convolutional Recurrent Neural Network
### URL
(https://tmpfiles.org/dl/3316673/yirnn.pdf)
### Summary
The paper by Jaehyuk Yi and Jinkyoo Park introduces a hypergraph co…
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Nice package, help me a lot~
I'm confused when testing the GS method and other BN algorithms. When only input data, edges in the generated graph are almost bi-directional. But when inputting data and…
XMAHA updated
2 years ago
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George D, et. al. [Clone-structured graph representations enable flexible learning and vicarious evaluation of cognitive maps](https://www.nature.com/articles/s41467-021-22559-5).
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Goal: the traditional graph mining data scientist can handle big data without learning too much new grammar.
[OpenCyph…
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Install pyStruct a graph based learning library that seems to be the only one that supports Tree Structures for Conditional Random Fields (t-CRFs)
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Structured data arises in a few of the domains discussed throughout the review. For example, CNNs perform tremendously for many tasks based on data from a regular graph like images ([subsection here](…
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Hello,
I'm trying to use causal-learn (pc and fci at the moment) but I'm stuck with input data errors.
My dataframe has no nans nor infs, as checked with both pandas and numpy, but running either…