Node Regression

Benchmarks archive 2025-07-28

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Libraries

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Datasets archive 2025-07-28

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

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Most implemented papers archive 2025-07-28

6 shown of 6 papers with code (13 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Fully Distributed Online Training of Graph Neural Networks in Networked Systems
  8 Dec 2024 1 repository listed
  Graph neural networks (GNNs) are powerful tools for developing scalable, decentralized artificial intelligence in large-scale networked systems, such as wireless networks, power grids, and transportation networks.
• FIT-GNN: Faster Inference Time for GNNs Using Coarsening
  19 Oct 2024 1 repository listed
  The results demonstrate that our method achieves competitive performance in tasks involving classification and regression on nodes and graphs, compared to traditional GNNs, while having single-node inference times that…
• Uplift Modeling Under Limited Supervision
  28 Mar 2024 1 repository listed
  Estimating causal effects in e-commerce tends to involve costly treatment assignments which can be impractical in large-scale settings.
• Infinite Width Graph Neural Networks for Node Regression/ Classification
  12 Oct 2023 1 repository listed
  This work analyzes Graph Neural Networks, a generalization of Fully-Connected Deep Neural Nets on Graph structured data, when their width, that is the number of nodes in each fullyconnected layer is increasing to…
• Propagation on Multi-relational Graphs for Node Regression
  15 Oct 2021 1 repository listed
  Recent years have witnessed a rise in real-world data captured with rich structural information that can be conveniently depicted by multi-relational graphs.
• Transfer Learning for Node Regression Applied to Spreading Prediction
  31 Mar 2021 1 repository listed
  This work is one of the first to explore transferability of the learned representations for the task of node regression; we show there exist pairs of networks with similar structure between which the trained models can…