Generalization bounds for graph convolutional neural networks via Rademacher complexity

20 February 2021

Papers citing "Generalization bounds for graph convolutional neural networks via Rademacher complexity"

5 / 5 papers shown

Title
SStaGCN: Simplified stacking based graph convolutional networks Jia Cai Zhilong Xiong Shaogao Lv GNN 38 1 0 16 Nov 2021
Learning on Random Balls is Sufficient for Estimating (Some) Graph Parameters Takanori Maehara Hoang NT 41 2 0 05 Nov 2021
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 280 1,400 0 01 Dec 2016
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 259 3,239 0 24 Nov 2016
Norm-Based Capacity Control in Neural Networks Behnam Neyshabur Ryota Tomioka Nathan Srebro 122 577 0 27 Feb 2015