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For improving the ability of GraphAr format, we prepare to construct a data hub with GraphAr format.
This issue is for gathering graph dataset, which is best to meet the following requirements:
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What are common algorithms that are important in detecting neural connectivity? Specifically, what analytics platforms are they on and how are they optimized?
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* [ ] 1. [Hierarchical Pooling in Graph Neural Networks to Enhance Classification Performance in Large Datasets](https://www.mdpi.com/1424-8220/21/18/6070/htm)
* [ ] 2. [Hierarchical Graph Pooling wi…
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## 🚀 Feature
Please add implementation for HGCN (https://github.com/HazyResearch/hgcn) and HGNN (https://github.com/facebookresearch/hgnn), if feasible and at your convenience.
## Motivation
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[Local collaborative autoencoders](https://sci-hub.ru/https://dl.acm.org/doi/abs/10.1145/3437963.3441808)
[Local latent space models for top-n recommendation](https://sci-hub.ru/https://dl.acm.org/do…
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Hi,
Are you interested in AI? Many are!
One thing indicated by the Genetic Programming research is, Graphs are more efficient than Trees because they can reuse nodes. In a tree you might have t…
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### Context
Neural networks are graphs consisting of nodes called operators. Each operator corresponds to a mathematical function, usually described in framework's documentation or an AI standard, …
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### Context
Neural networks are graphs consisting of nodes called operators. Each operator corresponds to a mathematical function, usually described in framework's documentation or an AI standard, …
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## Description
I'd like to suggest the implementation of implicit reparameterization gradients, as described in the paper [1], for the Gamma distribution: ndarray.sample_gamma and symbol.sample_gamma…
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TensorBoard collapses Relu-Relu_6 nodes together into one node which turns simple neural net graphs into a jumple
Example pbtxt [here](https://github.com/yaroslavvb/stuff/blob/master/resnet_8_simpl…