Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural
Networks

Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks

18 July 2022

Liang Ding

Danilo P. Mandic

Papers citing "Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural Networks"

8 / 8 papers shown

Title
Towards Faster and More Compact Foundation Models for Molecular Property Prediction Yasir Ghunaim Andrés Villa Gergo Ignacz Gyorgy Szekely Motasem Alfarra Bernard Ghanem AI4CE 84 0 0 28 Apr 2025
Embracing Unknown Step by Step: Towards Reliable Sparse Training in Real World Bowen Lei Dongkuan Xu Ruqi Zhang Bani Mallick UQCV 29 0 0 29 Mar 2024
Training Large Language Models Efficiently with Sparsity and Dataflow V. Srinivasan Darshan Gandhi Urmish Thakker R. Prabhakar MoE 28 6 0 11 Apr 2023
Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction Bowen Lei Dongkuan Xu Ruqi Zhang Shuren He Bani Mallick 25 6 0 09 Jan 2023
Graph Neural Networks for Graph Drawing Matteo Tiezzi Gabriele Ciravegna Marco Gori 21 20 0 21 Sep 2021
Sparsity in Deep Learning: Pruning and growth for efficient inference and training in neural networks Torsten Hoefler Dan Alistarh Tal Ben-Nun Nikoli Dryden Alexandra Peste MQ 139 684 0 31 Jan 2021
Beyond Low-frequency Information in Graph Convolutional Networks Deyu Bo Xiao Wang C. Shi Huawei Shen GNN 87 554 0 04 Jan 2021
The Lottery Ticket Hypothesis for Pre-trained BERT Networks Tianlong Chen Jonathan Frankle Shiyu Chang Sijia Liu Yang Zhang Zhangyang Wang Michael Carbin 148 345 0 23 Jul 2020