research
∙
09/16/2023
Invertible Mosaic Image Hiding Network for Very Large Capacity Image Steganography
The existing image steganography methods either sequentially conceal sec...
share
research
∙
06/20/2023
GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks
Graph structure learning is a well-established problem that aims at opti...
research
∙
06/14/2023
NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification
Graph neural networks have been extensively studied for learning with in...
research
∙
01/23/2023
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
Real-world data generation often involves complex inter-dependencies amo...
research
∙
11/28/2022
Imperceptible Adversarial Attack via Invertible Neural Networks
Adding perturbations via utilizing auxiliary gradient information or dis...
research
∙
12/19/2020
A pipeline for fair comparison of graph neural networks in node classification tasks
Graph neural networks (GNNs) have been investigated for potential applic...
research
∙
03/11/2018
