* feature: add a parse parameter degree_as_nlabel for pytorch-gin demo
* fix some typo
* [fix]: allow to benchmark all of the 9 dataset.
* [Feature] add epoch number to log
* [Feature]:simply list the command lines for all datasets (https://github.com/dmlc/dgl/pull/3676#discussion_r790270705) and run a test.
* Update README.md
* update: DGL-powered projects-DGLD
[DGLD](https://github.com/EagleLab-ZJU/DGLD) is an open-source library for Deep Graph Anomaly Detection based on pytorch and DGL. It provides unified interface of popular graph anomaly detection methods, including the data loader, data augmentation, model training and evaluation. Also, the widely used modules are well organized so that developers and researchers can quickly implement their own designed models.
Co-authored-by: Ubuntu <ubuntu@ip-172-31-10-175.ap-northeast-1.compute.internal>
Co-authored-by: Mufei Li <mufeili1996@gmail.com>
* Add RNAGlib to examples and DGL-powered-projects
* Add RNAGlib to examples and DGL-powered-projects
* Add RNAGlib to examples and DGL-powered-projects
* Added code for Rectifying (TypeError: unhashable type: 'slice') when copying file
* 1) added distributed preprocessing code to create ParMetis Input from CSV files
2) add code to run pm_dglpart on multiple machines
3) added support for recreating heteregenous graph from homo geneous graph based on dropped edges, as ParMetis currently only supports homogeneous graphs
* move to pandas
* Added comments and remove drop_duplicates as it was redundant
* Addressed Pr Comments
* Rename variable
* Added comment
* Added comment
* updated ReadMe
Co-authored-by: Ankit Garg <gaank@amazon.com>
Co-authored-by: Da Zheng <zhengda1936@gmail.com>
* PPIDataset
* Revert "PPIDataset"
This reverts commit 264bd0c960.
* data pipeline user guide
* remove chapter numbers
* Update data.rst
* image in dataset userguide
* update links using ref
* modify the link of save_graphs and load_graphs in dataset user guide
* move image to s3 server.
* fix links and ref
* Hide implementations that may cause confusions to the user
* add papers
* fix number of classes in Amazon Cobuy datasets
* add two papers to Awesome paper list
* Update README.md
* add four papers
* add two papers
* Add awesome papers
* Fix index in paper list
* Add paper to paperlist
* add two papers
* add two papers
* Update README.md
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
* PPIDataset
* Revert "PPIDataset"
This reverts commit 264bd0c960.
* data pipeline user guide
* remove chapter numbers
* Update data.rst
* image in dataset userguide
* update links using ref
* modify the link of save_graphs and load_graphs in dataset user guide
* move image to s3 server.
* fix links and ref
* Hide implementations that may cause confusions to the user
* add papers
* fix number of classes in Amazon Cobuy datasets
* add two papers to Awesome paper list
* Update README.md
* add four papers
* add two papers
* Add awesome papers
* Fix index in paper list
* Add paper to paperlist
* add two papers
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
* PPIDataset
* Revert "PPIDataset"
This reverts commit 264bd0c960.
* data pipeline user guide
* remove chapter numbers
* Update data.rst
* image in dataset userguide
* update links using ref
* modify the link of save_graphs and load_graphs in dataset user guide
* move image to s3 server.
* fix links and ref
* Hide implementations that may cause confusions to the user
* add papers
* fix number of classes in Amazon Cobuy datasets
* add two papers to Awesome paper list
* Update README.md
* add four papers
* add two papers
* Add awesome papers
* Fix index in paper list
Co-authored-by: Minjie Wang <wmjlyjemaine@gmail.com>
* PPIDataset
* Revert "PPIDataset"
This reverts commit 264bd0c960.
* data pipeline user guide
* remove chapter numbers
* Update data.rst
* image in dataset userguide
* update links using ref
* modify the link of save_graphs and load_graphs in dataset user guide
* move image to s3 server.
* fix links and ref
* Hide implementations that may cause confusions to the user
* add papers
* fix number of classes in Amazon Cobuy datasets
* add two papers to Awesome paper list
* Update README.md
* add four papers
* add two papers
* PPIDataset
* Revert "PPIDataset"
This reverts commit 264bd0c960.
* Hide implementations that may cause confusions to the user
* fix number of classes in Amazon Cobuy datasets
* add four papers
* PPIDataset
* Revert "PPIDataset"
This reverts commit 264bd0c960.
* data pipeline user guide
* remove chapter numbers
* Update data.rst
* image in dataset userguide
* update links using ref
* modify the link of save_graphs and load_graphs in dataset user guide
* move image to s3 server.
* fix links and ref
* Hide implementations that may cause confusions to the user
* add papers
* fix number of classes in Amazon Cobuy datasets
* add two papers to Awesome paper list
* Update README.md
