$$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks$

$\rm A^2Q$ : Aggregation-Aware Quantization for Graph Neural Networks

1 February 2023

Papers citing "$\rm A^2Q$: Aggregation-Aware Quantization for Graph Neural Networks"

5 / 5 papers shown

Title
Projected Stochastic Gradient Descent with Quantum Annealed Binary Gradients Maximilian Krahn Michele Sasdelli Fengyi Yang Vladislav Golyanik Juho Kannala Tat-Jun Chin Tolga Birdal MQ 67 2 0 23 Oct 2023
Low-bit Quantization for Deep Graph Neural Networks with Smoothness-aware Message Propagation Shuang Wang B. Eravcı Rustam Guliyev Hakan Ferhatosmanoglu GNN MQ 19 6 0 29 Aug 2023
Towards Mixed-Precision Quantization of Neural Networks via Constrained Optimization Weihan Chen Peisong Wang Jian Cheng MQ 31 61 0 13 Oct 2021
Not Half Bad: Exploring Half-Precision in Graph Convolutional Neural Networks John Brennan Stephen Bonner Amir Atapour-Abarghouei Philip T. G. Jackson B. Obara A. Mcgough GNN 7 3 0 23 Oct 2020
Benchmarking Graph Neural Networks Vijay Prakash Dwivedi Chaitanya K. Joshi Anh Tuan Luu T. Laurent Yoshua Bengio Xavier Bresson 189 914 0 02 Mar 2020