We stand with Ukraine

We stand with Ukraine

Wei Ju

Orcid: 0000-0001-9657-951X

According to our database¹, Wei Ju authored at least 59 papers between 2015 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Links

On csauthors.net:

Bibliography

2024

Learning Graph ODE for Continuous-Time Sequential Recommendation.

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IEEE Trans. Knowl. Data Eng., July, 2024

Toward Effective Semi-supervised Node Classification with Hybrid Curriculum Pseudo-labeling.

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ACM Trans. Multim. Comput. Commun. Appl., March, 2024

A Diffusion Model for POI Recommendation.

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ACM Trans. Inf. Syst., March, 2024

Self-supervised Graph-level Representation Learning with Adversarial Contrastive Learning.

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ACM Trans. Knowl. Discov. Data, February, 2024

CLEAR: Cluster-Enhanced Contrast for Self-Supervised Graph Representation Learning.

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IEEE Trans. Neural Networks Learn. Syst., January, 2024

Towards Semi-Supervised Universal Graph Classification.

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IEEE Trans. Knowl. Data Eng., January, 2024

Focus on informative graphs! Semi-supervised active learning for graph-level classification.

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Pattern Recognit., 2024

A Comprehensive Survey on Deep Graph Representation Learning.

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Neural Networks, 2024

COOL: A Conjoint Perspective on Spatio-Temporal Graph Neural Network for Traffic Forecasting.

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Inf. Fusion, 2024

DisenSemi: Semi-supervised Graph Classification via Disentangled Representation Learning.

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CoRR, 2024

MMEvalPro: Calibrating Multimodal Benchmarks Towards Trustworthy and Efficient Evaluation.

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CoRR, 2024

Towards Graph Contrastive Learning: A Survey and Beyond.

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CoRR, 2024

A Survey of Graph Neural Networks in Real world: Imbalance, Noise, Privacy and OOD Challenges.

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CoRR, 2024

GPS: Graph Contrastive Learning via Multi-scale Augmented Views from Adversarial Pooling.

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CoRR, 2024

PolyCF: Towards the Optimal Spectral Graph Filters for Collaborative Filtering.

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CoRR, 2024

A Survey on Graph Neural Networks in Intelligent Transportation Systems.

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CoRR, 2024

A Survey of Data-Efficient Graph Learning.

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Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Rank and Align: Towards Effective Source-free Graph Domain Adaptation.

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Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

Hypergraph-enhanced Dual Semi-supervised Graph Classification.

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Proceedings of the Forty-first International Conference on Machine Learning, 2024

PGODE: Towards High-quality System Dynamics Modeling.

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Proceedings of the Forty-first International Conference on Machine Learning, 2024

Evidential Self-Supervised Graph Representation Learning via Prototype-based Consistency.

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Proceedings of the ACM Turing Award Celebration Conference 2024, 2024

2023

Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts.

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IEEE Trans. Big Data, December, 2023

Joint User Scheduling, Power Configuration and Trajectory Planning Strategy for UAV-Aided WSNs.

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ACM Trans. Sens. Networks, February, 2023

Unsupervised graph-level representation learning with hierarchical contrasts.

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Neural Networks, January, 2023

Zero-shot Node Classification with Graph Contrastive Embedding Network.

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Trans. Mach. Learn. Res., 2023

RIGNN: A Rationale Perspective for Semi-supervised Open-world Graph Classification.

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Trans. Mach. Learn. Res., 2023

Few-shot Molecular Property Prediction via Hierarchically Structured Learning on Relation Graphs.

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Neural Networks, 2023

Graph ODE with Factorized Prototypes for Modeling Complicated Interacting Dynamics.

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CoRR, 2023

Redundancy-Free Self-Supervised Relational Learning for Graph Clustering.

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CoRR, 2023

FIMO: A Challenge Formal Dataset for Automated Theorem Proving.

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Chuanyang Zheng

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CoRR, 2023

Towards Long-Tailed Recognition for Graph Classification via Collaborative Experts.

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CoRR, 2023

A Comprehensive Survey on Deep Graph Representation Learning.

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CoRR, 2023

Robust Dancer: Long-term 3D Dance Synthesis Using Unpaired Data.

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CoRR, 2023

DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation.

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Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

A Feasibility Study on Textile Electrodes for Transcutaneous Electrical Nerve Stimulation.

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Aidan McConnell-Trevillion

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Sadeque Reza Khan

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Kianoush Nazarpour

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Proceedings of the 21st IEEE Interregional NEWCAS Conference, 2023

ALEX: Towards Effective Graph Transfer Learning with Noisy Labels.

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Proceedings of the 31st ACM International Conference on Multimedia, 2023

RAHNet: Retrieval Augmented Hybrid Network for Long-tailed Graph Classification.

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Proceedings of the 31st ACM International Conference on Multimedia, 2023

HOPE: High-order Graph ODE For Modeling Interacting Dynamics.

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Proceedings of the International Conference on Machine Learning, 2023

Dynamic Hypergraph Structure Learning for Traffic Flow Forecasting.

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Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Learning on Graphs under Label Noise.

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Proceedings of the IEEE International Conference on Acoustics, 2023

GLCC: A General Framework for Graph-Level Clustering.

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Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

GHNN: Graph Harmonic Neural Networks for semi-supervised graph-level classification.

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Neural Networks, 2022

Networks open the door to the success of technological entrepreneurship: a perspective on political skills.

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Kybernetes, 2022

Imbalanced heartbeat classification using EasyEnsemble technique and global heartbeat information.

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Biomed. Signal Process. Control., 2022

KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification.

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Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Improved Deep Unsupervised Hashing via Prototypical Learning.

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Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

TGNN: A Joint Semi-supervised Framework for Graph-level Classification.

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Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Building Conversational Diagnosis Systems for Fine-Grained Diseases Using Few Annotated Data.

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Proceedings of the Neural Information Processing - 29th International Conference, 2022

Kernel-based Substructure Exploration for Next POI Recommendation.

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Proceedings of the IEEE International Conference on Data Mining, 2022

DualGraph: Improving Semi-supervised Graph Classification via Dual Contrastive Learning.

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Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

DisenCite: Graph-Based Disentangled Representation Learning for Context-Specific Citation Generation.

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Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

A Note on Comparison of F-measures.

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CoRR, 2021

An Interpretation of Convolutional Neural Networks for Motif Finding from the View of Probability.

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Proceedings of the 33rd IEEE International Conference on Tools with Artificial Intelligence, 2021

Deep Supervised Hashing by Classification for Image Retrieval.

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Proceedings of the Neural Information Processing - 28th International Conference, 2021

2020

PGNet: Pipeline Guidance for Human Key-Point Detection.

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Entropy, 2020

2017

Single-Channel Sparse Non-Negative Blind Source Separation Method for Automatic 3-D Delineation of Lung Tumor in PET Images.

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IEEE J. Biomed. Health Informatics, 2017

2016

Correction to "Random Walk and Graph Cut for Co-Segmentation of Lung Tumor on PET-CT Images".

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IEEE Trans. Image Process., 2016

2015

Random Walk and Graph Cut for Co-Segmentation of Lung Tumor on PET-CT Images.

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IEEE Trans. Image Process., 2015

Graph cut based co-segmentation of lung tumor in PET-CT images.

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Proceedings of the Medical Imaging 2015: Image Processing, 2015

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