RR-GCN | Code for R-GCN : The R Could Stand for Random

 by   predict-idlab Python Version: Current License: Non-SPDX

kandi X-RAY | RR-GCN Summary

kandi X-RAY | RR-GCN Summary

RR-GCN is a Python library. RR-GCN has no bugs, it has no vulnerabilities, it has build file available and it has low support. However RR-GCN has a Non-SPDX License. You can install using 'pip install RR-GCN' or download it from GitHub, PyPI.

Code for "R-GCN: The R Could Stand for Random"
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            kandi-support Support

              RR-GCN has a low active ecosystem.
              It has 16 star(s) with 1 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 0 open issues and 1 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of RR-GCN is current.

            kandi-Quality Quality

              RR-GCN has no bugs reported.

            kandi-Security Security

              RR-GCN has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              RR-GCN has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              RR-GCN releases are not available. You will need to build from source code and install.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions, examples and code snippets are available.

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            RR-GCN Key Features

            No Key Features are available at this moment for RR-GCN.

            RR-GCN Examples and Code Snippets

            No Code Snippets are available at this moment for RR-GCN.

            Community Discussions

            No Community Discussions are available at this moment for RR-GCN.Refer to stack overflow page for discussions.

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install RR-GCN

            After installing the correct PyG version for your PyTorch/CUDA installation as documented in their installation instructions, install the RR-GCN package using:.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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            CLONE
          • HTTPS

            https://github.com/predict-idlab/RR-GCN.git

          • CLI

            gh repo clone predict-idlab/RR-GCN

          • sshUrl

            git@github.com:predict-idlab/RR-GCN.git

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