Hello there, this video is great. Especially the way how you compare each library and explained it to us. I just wanted to ask something, but before that I want to say that I'm still new at this topic. So here's the question, does the dataset used in graph search / theory same as GCN want? What I mean is the type of dataset, like the structure
Hi, Yes the dataset is in form of a graph with nodes and edges, if this is your question. I also have a video on how to build such a dataset on my channel :) let me know if u have more questions
thank you for your video I am doing a deep dive on GNN and which options are available. I’m sure there are new ones now 😊. Which GNN model is best suited for live graph use cases?
Thanks, for such great content. I am working on MultiVariate Time Series Anomaly Detection using GNNs, Transformers, and GANs, do you know of any resource where I can start? I searched a lot but couldn't find anything other than papers, which are not that useful. Thanks again.
Hi! There is an article that might give you some ideas: medium.com/walmartglobaltech/an-overview-of-graph-neural-networks-for-anomaly-detection-in-e-commerce-b4c165b8f08a Also, have you seen this Github repo? github.com/safe-graph/DGFraud-TF2 They also have some resources on anomaly / outlier detection. Finally I have seen this collection, which might be interesting as well: github.com/xiaomingaaa/GNNApp-Papers :)
The quality of your videos about graph are sooo good.
Hello there, this video is great. Especially the way how you compare each library and explained it to us. I just wanted to ask something, but before that I want to say that I'm still new at this topic. So here's the question, does the dataset used in graph search / theory same as GCN want? What I mean is the type of dataset, like the structure
Hi,
Yes the dataset is in form of a graph with nodes and edges, if this is your question. I also have a video on how to build such a dataset on my channel :) let me know if u have more questions
stellargraph is another good library too
thank you for your video I am doing a deep dive on GNN and which options are available. I’m sure there are new ones now 😊. Which GNN model is best suited for live graph use cases?
Does PyG support weighted graph? If no, is there any of that 3 support for weighted graph?
Thank you so much Great work
best
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Fantastic rundown
great ! very helpful thanks for your work!
Thanks, for such great content.
I am working on MultiVariate Time Series Anomaly Detection using GNNs, Transformers, and GANs, do you know of any resource where I can start?
I searched a lot but couldn't find anything other than papers, which are not that useful.
Thanks again.
Hi!
There is an article that might give you some ideas: medium.com/walmartglobaltech/an-overview-of-graph-neural-networks-for-anomaly-detection-in-e-commerce-b4c165b8f08a
Also, have you seen this Github repo? github.com/safe-graph/DGFraud-TF2
They also have some resources on anomaly / outlier detection.
Finally I have seen this collection, which might be interesting as well: github.com/xiaomingaaa/GNNApp-Papers
:)
You are my teacher please add the data to your github. Thank you for everything
Hi! Thanks :) I have not saved any code for this video. These were just samples from the documentation :)
Great video! Can these library also explain features impact on target variable?
Hi! Most of them only implement the GNN Explainer. DiveIntoGraphs has further explainability methods. I also made a video about this recently :)