Interpretable Sparsification of Brain Graphs: Better Practices and
Effective Designs for Graph Neural Networks

Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks

26 June 2023

Yujun Yan

Papers citing "Interpretable Sparsification of Brain Graphs: Better Practices and Effective Designs for Graph Neural Networks"

8 / 8 papers shown

Title
Exploring Consistency in Graph Representations:from Graph Kernels to Graph Neural Networks Xuyuan Liu Yinghao Cai Qihui Yang Yujun Yan 31 0 0 31 Oct 2024
Graph Sparsification for Enhanced Conformal Prediction in Graph Neural Networks Yuntian He Pranav Maneriker Anutam Srinivasan Aditya T. Vadlamani Srinivasan Parthasarathy 28 0 0 28 Oct 2024
Sparse Covariance Neural Networks Andrea Cavallo Zhan Gao Elvin Isufi 28 1 0 02 Oct 2024
Graph Neural Networks for Brain Graph Learning: A Survey Xuexiong Luo Jia Wu Jian Yang Shan Xue Amin Beheshti Quan Z. Sheng David Mcalpine Paul F. Sowman Alexis Giral Philip S. Yu AI4CE 18 4 0 01 Jun 2024
A Comprehensive Survey on Graph Reduction: Sparsification, Coarsening, and Condensation Mohammad Hashemi Shengbo Gong Juntong Ni Wenqi Fan B. A. Prakash Wei-dong Jin DD 64 39 0 29 Jan 2024
VCISR: Blind Single Image Super-Resolution with Video Compression Synthetic Data Boyang Wang Bowen Liu Shiyu Liu Fengyu Yang 16 7 0 02 Nov 2023
Boosting Detection in Crowd Analysis via Underutilized Output Features Shaokai Wu Fengyu Yang 30 15 0 30 Aug 2023
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 164 591 0 31 Dec 2020