From d7f4ce2ac979b40f69ca8d82d097292be3dc77f3 Mon Sep 17 00:00:00 2001
From: Lin Manxi <46046604+mmmmimic@users.noreply.github.com>
Date: Fri, 1 Jan 2021 23:01:16 +0100
Subject: [PATCH] Update README.md

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-# DIFF GRAPH U-NET: A DIFFERENTIAL U-SHAPE NETWORK FOR GRAPH CLASSIFICATION
+# DIFF GRAPH U-NET: A DIFFERENTIABLE U-SHAPE NETWORK FOR GRAPH CLASSIFICATION
 ## Introduction
 Regarding GCNs, there are mainly three tasks: node classification, link prediction, and graph classification. This project focuses on the classification of graphics through Differentiable Pooling (DIFFPOOL). DIFFPOOL is a state-of-the-art pool module that can learn the hierarchical expression of graphics and combine various end-to-end GCN structures. Hence, in order to research the changes of a graph after several DIFFPOOL modules respectively, the visualizations for pooling has been fulfilled via rebuilding the graph. Apart from DIFFPOOL, this project also explored the possibility to build an encoder-decoder architecture via building such a U-net-like method for graph data. A novel GCN architecture DIFF Graph U-Net is proposed. 
 
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