科研进展:修订间差异

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Iip1314​(留言 | 贡献)
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'''<span style="font-family:微软雅黑; font-size:medium">Selected Paper</span>'''
'''<span style="font-family:微软雅黑; font-size:medium">Selected Paper</span>'''
<p style="text-align:center"><span style="font-family:Times New Roman,Times,serif"><span style="font-size:larger">2022</span></span></p>  
<p style="text-align:center"><span style="font-family:Times New Roman,Times,serif"><span style="font-size:larger">2022</span></span></p>  
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Du Y., Luo H., Yang H.,&nbsp;&nbsp;Jiang J. and&nbsp;etc.&nbsp;InCo: Intermediate Prototype Contrast for Unsupervised Domain Adaptation.&nbsp;</span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">In&nbsp;'''''Proceedings of&nbsp;'''''</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">&nbsp;'''''ECML PKDD''''', Accepted</span></span>
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Xu M. etc.&nbsp;NED-GNN: Detecting and Dropping Noisy Edges in Graph Neural Networks.&nbsp;</span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">In&nbsp;'''''Proceedings of&nbsp;'''''</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">&nbsp;'''''APWeb-WAIM''''', Accepted</span></span>  
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Xu M. etc.&nbsp;NED-GNN: Detecting and Dropping Noisy Edges in Graph Neural Networks.&nbsp;</span></span><span style="font-size:medium;"><span style="font-family:Times New Roman,Times,serif;">In&nbsp;'''''Proceedings of&nbsp;'''''</span></span><span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">&nbsp;'''''APWeb-WAIM''''', Accepted</span></span>  
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Xu M. etc.&nbsp;NC-GNN: Consistent Neighbors of Nodes Help More in Graph Neural Networks.'''''Wireless Communications and Mobile Computing''''', Accepted</span></span>  
#<span style="font-family:Times New Roman,Times,serif;"><span style="font-size:medium;">Xu M. etc.&nbsp;NC-GNN: Consistent Neighbors of Nodes Help More in Graph Neural Networks.'''''Wireless Communications and Mobile Computing''''', Accepted</span></span>