Search Results for author: Vijay Prakash Dwivedi

Found 6 papers, 6 papers with code

Long Range Graph Benchmark

1 code implementation16 Jun 2022 Vijay Prakash Dwivedi, Ladislav Rampášek, Mikhail Galkin, Ali Parviz, Guy Wolf, Anh Tuan Luu, Dominique Beaini

Graph Neural Networks (GNNs) that are based on the message passing (MP) paradigm generally exchange information between 1-hop neighbors to build node representations at each layer.

Graph Classification Graph Learning +3

Recipe for a General, Powerful, Scalable Graph Transformer

1 code implementation25 May 2022 Ladislav Rampášek, Mikhail Galkin, Vijay Prakash Dwivedi, Anh Tuan Luu, Guy Wolf, Dominique Beaini

We propose a recipe on how to build a general, powerful, scalable (GPS) graph Transformer with linear complexity and state-of-the-art results on a diverse set of benchmarks.

Graph Classification Graph Property Prediction +3

A Generalization of Transformer Networks to Graphs

1 code implementation17 Dec 2020 Vijay Prakash Dwivedi, Xavier Bresson

This work closes the gap between the original transformer, which was designed for the limited case of line graphs, and graph neural networks, that can work with arbitrary graphs.

Graph Regression Inductive Bias +3

Benchmarking Graph Neural Networks

12 code implementations2 Mar 2020 Vijay Prakash Dwivedi, Chaitanya K. Joshi, Anh Tuan Luu, Thomas Laurent, Yoshua Bengio, Xavier Bresson

In the last few years, graph neural networks (GNNs) have become the standard toolkit for analyzing and learning from data on graphs.

Graph Classification Graph Regression +2

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