This is the Windows app named Literature of Deep Learning for Graphs whose latest release can be downloaded as LiteratureDL4Graphsourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Literature of Deep Learning for Graphs with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS:
Literature of Deep Learning for Graphs
DESCRIPTION:
Literature of Deep Learning for Graphs is a curated repository that collects research papers and educational resources related to deep learning methods for graph-structured data. The project organizes important academic work covering topics such as graph neural networks, graph embeddings, knowledge graphs, and network representation learning. By structuring the literature into categories, the repository allows researchers to quickly identify influential papers in specific subfields of graph machine learning. The collection includes foundational works that introduced graph convolutional networks as well as more recent research on large-scale graph representation learning and graph generation techniques. The repository is designed as a reference guide for students and researchers who want to explore the rapidly growing field of graph deep learning.
Features
- Curated list of research papers on deep learning for graph data
- Coverage of graph neural networks, embeddings, and network representation learning
- Organization of literature by topic and research area
- Resources related to knowledge graphs and large-scale graph analysis
- Reference hub for researchers studying graph machine learning
- Continuously updated collection of influential graph ML papers
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/literature-of-dl-graphs.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.