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Yibing Zhan

Showing results (11-20 of 18) with videos related to

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Neural Networks : the Official Journal of the International Neural Network Society|October 14, 2023
Graph structure reforming framework enhanced by commute time distance for graph classificationWenhang Yu, Xueqi Ma, James Bailey, et al.
Neural Networks : the Official Journal of the International Neural Network Society|September 11, 2023
On exploring node-feature and graph-structure diversities for node drop graph poolingChuang Liu, Yibing Zhan, Baosheng Yu, et al.
Neural Networks : the Official Journal of the International Neural Network Society|October 18, 2024
Graph explicit pooling for graph-level representation learningChuang Liu, Wenhang Yu, Kuang Gao, et al.
Neural Networks : the Official Journal of the International Neural Network Society|August 22, 2024
Finding core labels for maximizing generalization of graph neural networksSichao Fu, Xueqi Ma, Yibing Zhan, et al.
Neural Networks : the Official Journal of the International Neural Network Society|March 29, 2024
Exploring sparsity in graph transformersChuang Liu, Yibing Zhan, Xueqi Ma, et al.
IEEE Transactions on Neural Networks and Learning Systems|June 27, 2023
Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural NetworksChuang Liu, Xueqi Ma, Yibing Zhan, et al.
Neural Networks : the Official Journal of the International Neural Network Society|September 14, 2025
DA-MoE: Addressing depth-sensitivity in graph-level analysis through mixture of expertsZelin Yao, Mukun Chen, Chuang Liu, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|July 18, 2025
Aligning Text-to-Image Diffusion Models with Constrained Reinforcement LearningZiyi Zhang, Sen Zhang, Li Shen, et al.
Pageof 2

Showing results (11-20 of 18) with videos related to

Sort By:
Pageof 2
You have reached the last page of results.This site can display upto 18 results.
Neural Networks : the Official Journal of the International Neural Network Society|October 14, 2023
Graph structure reforming framework enhanced by commute time distance for graph classificationWenhang Yu, Xueqi Ma, James Bailey, et al.
Neural Networks : the Official Journal of the International Neural Network Society|September 11, 2023
On exploring node-feature and graph-structure diversities for node drop graph poolingChuang Liu, Yibing Zhan, Baosheng Yu, et al.
Neural Networks : the Official Journal of the International Neural Network Society|October 18, 2024
Graph explicit pooling for graph-level representation learningChuang Liu, Wenhang Yu, Kuang Gao, et al.
Neural Networks : the Official Journal of the International Neural Network Society|August 22, 2024
Finding core labels for maximizing generalization of graph neural networksSichao Fu, Xueqi Ma, Yibing Zhan, et al.
Neural Networks : the Official Journal of the International Neural Network Society|March 29, 2024
Exploring sparsity in graph transformersChuang Liu, Yibing Zhan, Xueqi Ma, et al.
IEEE Transactions on Neural Networks and Learning Systems|June 27, 2023
Comprehensive Graph Gradual Pruning for Sparse Training in Graph Neural NetworksChuang Liu, Xueqi Ma, Yibing Zhan, et al.
Neural Networks : the Official Journal of the International Neural Network Society|September 14, 2025
DA-MoE: Addressing depth-sensitivity in graph-level analysis through mixture of expertsZelin Yao, Mukun Chen, Chuang Liu, et al.
IEEE Transactions on Pattern Analysis and Machine Intelligence|July 18, 2025
Aligning Text-to-Image Diffusion Models with Constrained Reinforcement LearningZiyi Zhang, Sen Zhang, Li Shen, et al.
Pageof 2