• A Tutorial on Network Embeddings, H. Chen et al.: https://arxiv.org/abs/1808.02590
• Asymmetric Transitivity Preserving Graph Embedding, M. Ou et al.: https://www.kdd.org/kdd2016/papers/files/rfp0184-ouA.pdf
• The paper behind karateclub:
  An API Oriented Open Source Python Framework for Unsupervised Learning on Graphs, B. Rozemberczki et al.: https://arxiv.org/abs/2003.04819
• Paper introducing DeepWalk: Online Learning of Social Representations, B. Perozzi et al.: https://arxiv.org/abs/1403.6652
• node2vec: Scalable Feature Learning for Networks, A. Grover et al., ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 201: https://arxiv.org/abs/1607.00653
• You will find a deeper introduction to GNNs in:
• Chapter 13 of Advanced Deep Learning with Python, I. Vasilev, Packt Publishing.
• Graph Neural Networks: A Review of Methods and Applications, J. Zhou et al.: https://arxiv.org/abs/1812.08434
• A Comprehensive Survey on Graph Neural Networks, Z. Wu et al...