Graph contrastivelearning (GCL), by training GNNs to maximize the correspondence between the representations of the same graph in its different augmented forms, may yield robust and transferable GNNs even without using labels.

These processes find wide application in the natural sciences and machine learning, but their inference is known to be far from trivial.

Which transformer scaling regimes are able to perfectly solve different classes of algorithmic problems?

MPNNs, graph transformers do not rely on fixed graph structure information.

Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/

Neural Information Processing Systems http://nips.cc/

PageRank (PR), an algorithm originally proposed by Page et al. for ranking web-pages [1] has found manysuccessful applications, including community detection [2,3],linkprediction [4]and recommendersystemdesign[5,6].