most citedGraph Fairing Convolutional Networks for Anomaly Detection

3 citations · 3 across the 2 of their papers we have counts for

collaborators

3 papers

cs.LG2023

A Graph Encoder-Decoder Network for Unsupervised Anomaly Detection

Mahsa Mesgaran, A. Ben Hamza

A key component of many graph neural networks (GNNs) is the pooling operation, which seeks to reduce the size of a graph while preserving important structural information. However,…

cs.LG2020

Anisotropic Graph Convolutional Network for Semi-supervised Learning

Mahsa Mesgaran, A. Ben Hamza

Graph convolutional networks learn effective node embeddings that have proven to be useful in achieving high-accuracy prediction results in semi-supervised learning tasks, such as…

cs.LG2020★ 3 cited

Graph Fairing Convolutional Networks for Anomaly Detection

Mahsa Mesgaran, A. Ben Hamza

Graph convolution is a fundamental building block for many deep neural networks on graph-structured data. In this paper, we introduce a simple, yet very effective graph convolution…