Search Results for author: Chengbin Hou

Found 8 papers, 6 papers with code

Fossil Image Identification using Deep Learning Ensembles of Data Augmented Multiviews

2 code implementations16 Feb 2023 Chengbin Hou, Xinyu Lin, Hanhui Huang, Sheng Xu, Junxuan Fan, Yukun Shi, Hairong Lv

Besides, OGS obtains the superior or comparable performance compared to the method under well-known bagging framework.

Image Classification

Recent Advances in Reliable Deep Graph Learning: Inherent Noise, Distribution Shift, and Adversarial Attack

no code implementations15 Feb 2022 Jintang Li, Bingzhe Wu, Chengbin Hou, Guoji Fu, Yatao Bian, Liang Chen, Junzhou Huang, Zibin Zheng

Despite the progress, applying DGL to real-world applications faces a series of reliability threats including inherent noise, distribution shift, and adversarial attacks.

Adversarial Attack Graph Learning

Robust Dynamic Network Embedding via Ensembles

3 code implementations30 May 2021 Chengbin Hou, Guoji Fu, Peng Yang, Zheng Hu, Shan He, Ke Tang

It is natural to ask if existing DNE methods can perform well for an input dynamic network without smooth changes.

Network Embedding

GloDyNE: Global Topology Preserving Dynamic Network Embedding

2 code implementations5 Aug 2020 Chengbin Hou, Han Zhang, Shan He, Ke Tang

The main and common objective of Dynamic Network Embedding (DNE) is to efficiently update node embeddings while preserving network topology at each time step.

Graph Reconstruction Incremental Learning +1

DynWalks: Global Topology and Recent Changes Awareness Dynamic Network Embedding

2 code implementations arXiv 2019 Chengbin Hou, Han Zhang, Ke Tang, Shan He

Dynamic network embedding aims to learn low dimensional embeddings for unseen and seen nodes by using any currently available snapshots of a dynamic network.

Graph Reconstruction Link Prediction +1

Learning Topological Representation for Networks via Hierarchical Sampling

1 code implementation15 Feb 2019 Guoji Fu, Chengbin Hou, Xin Yao

To tackle this issue, we propose a new NRL framework, named HSRL, to help existing NRL methods capture both the local and global topological information of a network.

Link Prediction Representation Learning

Attributed Network Embedding for Incomplete Attributed Networks

1 code implementation28 Nov 2018 Chengbin Hou, Shan He, Ke Tang

Attributed networks are ubiquitous since a network often comes with auxiliary attribute information e. g. a social network with user profiles.

Link Prediction Network Embedding +1

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