mlsanityData to 14 Oct 2026

Evolving-Graph Gaussian Processes

arXiv 2106.15127 ↗First posted 29 Jun 2021cs.LG stat.ML stat.OTcited by 1

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Abstract (arXiv)

Graph Gaussian Processes (GGPs) provide a data-efficient solution on graph structured domains. Existing approaches have focused on static structures, whereas many real graph data represent a dynamic structure, limiting the applications of GGPs. To overcome this we propose evolving-Graph Gaussian Processes (e-GGPs). The proposed method is capable of learning the transition function of graph vertices over time with a neighbourhood kernel to model the connectivity and interaction changes between vertices. We assess the performance of our method on time-series regression problems where graphs evolve over time. We demonstrate the benefits of e-GGPs over static graph Gaussian Process approaches.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 14 of its 27 references that are in the map. First posted on arXiv 29 Jun 2021.

Builds on

14 of 27 references.

References · 14

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  2. 2018GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Accelerationcited by 609
  3. 2018Graph networks as learnable physics engines for inference and controlcited by 244
  4. 2018Learning Particle Dynamics for Manipulating Rigid Bodies, Deformable Objects, and Fluidscited by 220
  5. 2017Cautious Model Predictive Control using Gaussian Process Regressioncited by 91
  6. 2020Mat'ern Gaussian Processes on Graphscited by 66
  7. 2017Convolutional Gaussian Processescited by 44
  8. 2018Bayesian Semi-supervised Learning with Graph Gaussian Processescited by 28
  9. 2020Gaussian Processes on Graphs via Spectral Kernel Learningcited by 24
  10. 2019Graph Convolutional Gaussian Processescited by 20
  11. 2018Gaussian Processes Over Graphscited by 14
  12. 2018The Gaussian Process Autoregressive Regression Model (GPAR)cited by 12
2 more
  1. 2015Recurrent Gaussian Processescited by 9
  2. 2020Graph Convolutional Gaussian Processes For Link Predictioncited by 8

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Citing papers per year: 2026: 1.

1 paper.

  1. 2026Laplacian Kernelized Banditcited by 1