Huiyan Sun

Orcid: 0000-0002-4664-7147

According to our database1, Huiyan Sun authored at least 24 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
De-confounding representation learning for counterfactual inference on continuous treatment via generative adversarial network.
Data Min. Knowl. Discov., November, 2024

Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data.
ACM Trans. Knowl. Discov. Data, April, 2024

A General Causal Inference Framework for Cross-Sectional Observational Data.
CoRR, 2024

SLIVER: Unveiling large scale gene regulatory networks of single-cell transcriptomic data through causal structure learning and modules aggregation.
Comput. Biol. Medicine, 2024

ScMOGAE: A Graph Convolutional Autoencoder-Based Multi-omics Data Integration Framework for Single-Cell Clustering.
Proceedings of the Bioinformatics Research and Applications - 20th International Symposium, 2024

Process optimization and cryogenic evaluation of spin-orbit torque magnetic random access memory.
Proceedings of the IEEE International Memory Workshop, 2024

Estimating Individual Causal Treatment Effect by Variable Decomposition.
Proceedings of the International Joint Conference on Neural Networks, 2024

2023
Gene regulatory network inference based on causal discovery integrating with graph neural network.
Quant. Biol., December, 2023

A Study on the Impact of Non-confounding Covariates on the Inferential Performance of Methods based on the Potential Outcome Framework.
CoRR, 2023

VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference.
CoRR, 2023

De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network.
CoRR, 2023

Improve Robustness of Graph Neural Networks: Multi-hop Neighbors Meet Homophily-based Truncation Defense.
Proceedings of the International Joint Conference on Neural Networks, 2023

Contrastive self-supervised graph convolutional network for detecting the relationship among lncRNAs, miRNAs, and diseases.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2023

2022
Identification of key somatic oncogenic mutation based on a confounder-free causal inference model.
PLoS Comput. Biol., September, 2022

SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2022

2021
The bioinformatics toolbox for circRNA discovery and analysis.
Briefings Bioinform., 2021

A Breast Cancer Patients' Survival Prediction Model Using mRMR Feature Selection with Artificial Neural Network.
Proceedings of the CSAE 2021: The 5th International Conference on Computer Science and Application Engineering, Sanya, China, October 19, 2021

An AutoEncoder-Based Matrix Factorization Approach to Estimating Cell Proportion from Bulk Tumor RNA-seq Data.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020
Identification of Cancer Development Related Pathways Based on Co-Expression Analyses.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2020

Unsupervised Nonlinear Feature Selection from High-Dimensional Signed Networks.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Warburg Effects in Cancer and Normal Proliferating Cells: Two Tales of the Same Name.
Genom. Proteom. Bioinform., 2019

Trends in the development of miRNA bioinformatics tools.
Briefings Bioinform., 2019

Multi-Classification of Cancer Samples Based on Co-Expression Analyses.
Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

2014
Essential protein identification based on essential protein-protein interaction prediction by integrated edge weights.
Proceedings of the 2014 IEEE International Conference on Bioinformatics and Biomedicine, 2014


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