Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using
Self-supervised Edge Features and Graph Neural Networks

Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks

23 June 2020

Arijit Sehanobish

David van Dijk

Papers citing "Gaining Insight into SARS-CoV-2 Infection and COVID-19 Severity Using Self-supervised Edge Features and Graph Neural Networks"

9 / 9 papers shown

Title
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks Wei-Lin Chiang Xuanqing Liu Si Si Yang Li Samy Bengio Cho-Jui Hsieh GNN 108 1,268 0 20 May 2019
A Comparative Study for Unsupervised Network Representation Learning Megha Khosla Vinay Setty Avishek Anand SSL 59 54 0 19 Mar 2019
GNNExplainer: Generating Explanations for Graph Neural Networks Rex Ying Dylan Bourgeois Jiaxuan You Marinka Zitnik J. Leskovec LLMAG 109 1,300 0 10 Mar 2019
Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks Juho Lee Yoonho Lee Jungtaek Kim Adam R. Kosiorek Seungjin Choi Yee Whye Teh 62 274 0 01 Oct 2018
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction Leland McInnes John Healy James Melville 113 9,312 0 09 Feb 2018
Learning Edge Representations via Low-Rank Asymmetric Projections Sami Abu-El-Haija Bryan Perozzi Rami Al-Rfou 43 76 0 16 May 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 123 3,848 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 115 5,920 0 04 Mar 2017
Layer Normalization Jimmy Lei Ba J. Kiros Geoffrey E. Hinton 246 10,412 0 21 Jul 2016