[D] Laplacian positional encodings

• graphtransformer

  4 804 0.0 Python

  Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.

  

I just finished reading "Benchmarking Graph Neural Networks" (Dwivedi et al. 2020) and "A Generalization of Transformer Networks to Graphs" (also Dwivedi et al. 2020), and came across the claim that Laplacian eigenvectors of a graph "represent a natural generalization of the Transformer (Vaswani et al., 2017) positional encodings (PE)". Xavier Bresson tweeted the same thing.

• benchmarking-gnns

  1 2,426 0.0 Jupyter Notebook

  Repository for benchmarking graph neural networks

  

Code for https://arxiv.org/abs/2003.00982 found: https://github.com/graphdeeplearning/benchmarking-gnns

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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