Hao Zhang

Orcid: 0000-0001-5544-5347

Affiliations:

Guangdong University of Petrochemical Technology, School of Computer, Maoming, China
Fudan University, School of Computer Science, Shanghai, China (PhD 2019)

According to our database¹, Hao Zhang authored at least 32 papers between 2016 and 2025.

Collaborative distances:

Dijkstra number² of five.
Erdős number³ of four.

Timeline

Legend:

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In proceedings

Article

PhD thesis

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Other

Bibliography

2025

Score-based Generative Modeling for Conditional Independence Testing.

[BibT_eX]

[DOI]

CoRR, May, 2025

Source-free domain adaptation based on label reliability for cross-domain bearing fault diagnosis.

[BibT_eX]

[DOI]

CoRR, March, 2025

GCCNet: A Novel Network Leveraging Gated Cross-Correlation for Multi-View Classification.

[BibT_eX]

[DOI]

IEEE Trans. Multim., 2025

Regression-based conditional independence test with adaptive kernels.

[BibT_eX]

[DOI]

Artif. Intell., 2025

Fast Causal Discovery by Approximate Kernel-based Generalized Score Functions with Linear Computational Complexity.

[BibT_eX]

[DOI]

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

2024

Towards Effective Causal Partitioning by Edge Cutting of Adjoint Graph.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., December, 2024

Hybrid Causal Feature Selection for Cancer Biomarker Identification From RNA-Seq Data.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2024

CDRM: Causal disentangled representation learning for missing data.

[BibT_eX]

[DOI]

Knowl. Based Syst., 2024

Efficiently Learning Significant Fourier Feature Pairs for Statistical Independence Testing.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Learning Adaptive Kernels for Statistical Independence Tests.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Conditional Independence Test Based on Residual Similarity.

[BibT_eX]

[DOI]

ACM Trans. Knowl. Discov. Data, 2023

Causal Gene Identification Using Non-Linear Regression-Based Independence Tests.

[BibT_eX]

[DOI]

IEEE ACM Trans. Comput. Biol. Bioinform., 2023

Causal Discovery by Continuous Optimization with Conditional Independence Constraint: Methodology and Performance.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2023

GEP-DL4Mol: A Novel Molecular Deep-learning Model Optimization Framework for Boosting Molecular Properties Prediction<sup>*</sup>.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

Multi-Level Wavelet Mapping Correlation for Statistical Dependence Measurement: Methodology and Performance.

[BibT_eX]

[DOI]

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

Differentially Private Nonlinear Causal Discovery from Numerical Data.

[BibT_eX]

[DOI]

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

2022

Learning Causal Structures Based on Divide and Conquer.

[BibT_eX]

[DOI]

IEEE Trans. Cybern., 2022

An automatic hyperparameter optimization DNN model for precipitation prediction.

[BibT_eX]

[DOI]

Appl. Intell., 2022

Residual Similarity Based Conditional Independence Test and Its Application in Causal Discovery.

[BibT_eX]

[DOI]

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

2021

Combined cause inference: Definition, model and performance.

[BibT_eX]

[DOI]

Inf. Sci., 2021

Person Re-Identification With Character-Illustration-Style Image and Normal Photo.

[BibT_eX]

[DOI]

IEEE Access, 2021

Testing Independence Between Linear Combinations for Causal Discovery.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Enhanced Graph Isomorphism Network for Molecular ADMET Properties Prediction.

[BibT_eX]

[DOI]

IEEE Access, 2020

2019

Measuring Conditional Independence by Independent Residuals for Causal Discovery.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2019

An Extreme Learning Machine and Gene Expression Programming-Based Hybrid Model for Daily Precipitation Prediction.

[BibT_eX]

[DOI]

Int. J. Comput. Intell. Syst., 2019

A Hybrid Precipitation Prediction Method based on Multicellular Gene Expression Programming.

[BibT_eX]

[DOI]

CoRR, 2019

A Seft-adaptive Multicellular GEP Algorithm Based On Fuzzy Control For Function Optimization.

[BibT_eX]

[DOI]

CoRR, 2019

Recursively Learning Causal Structures Using Regression-Based Conditional Independence Test.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018

Multicellular Gene Expression Programming-Based Hybrid Model for Precipitation Prediction Coupled with EMD.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Computing Theories and Application, 2018

Measuring Conditional Independence by Independent Residuals: Theoretical Results and Application in Causal Discovery.

[BibT_eX]

[DOI]

Hao Zhang

Shuigeng Zhou

Jihong Guan

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017

Causal Discovery Using Regression-Based Conditional Independence Tests.

[BibT_eX]

[DOI]

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Exploiting Twitter Moods to Boost Financial Trend Prediction Based on Deep Network Models.

[BibT_eX]

[DOI]

Proceedings of the Intelligent Computing Methodologies - 12th International Conference, 2016

Hao Zhang

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