Hao Yuan

Orcid: 0000-0001-5270-2782

Affiliations:

Texas A&M University, Department of Computer Science and Engineering, College Station, TX, USA (PhD 2021)

According to our database¹, Hao Yuan authored at least 22 papers between 2017 and 2024.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of three.

Timeline

Legend:

Book

In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2024

FlowX: Towards Explainable Graph Neural Networks via Message Flows.

[BibT_eX]

[DOI]

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

2023

Explainability in Graph Neural Networks: A Taxonomic Survey.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., May, 2023

Towards Improved and Interpretable Deep Metric Learning via Attentive Grouping.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2023

2022

Interpreting Image Classifiers by Generating Discrete Masks.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2022

2021

DIG: A Turnkey Library for Diving into Graph Deep Learning Research.

[BibT_eX]

[DOI]

J. Mach. Learn. Res., 2021

Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks.

[BibT_eX]

[DOI]

CoRR, 2021

Node2Seq: Towards Trainable Convolutions in Graph Neural Networks.

[BibT_eX]

[DOI]

Hao Yuan

Shuiwang Ji

CoRR, 2021

On Explainability of Graph Neural Networks via Subgraph Explorations.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Global Pixel Transformers for Virtual Staining of Microscopy Images.

[BibT_eX]

[DOI]

IEEE Trans. Medical Imaging, 2020

Pixel Transposed Convolutional Networks.

[BibT_eX]

[DOI]

IEEE Trans. Pattern Anal. Mach. Intell., 2020

XGNN: Towards Model-Level Explanations of Graph Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Deep Learning of High-Order Interactions for Protein Interface Prediction.

[BibT_eX]

[DOI]

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

StructPool: Structured Graph Pooling via Conditional Random Fields.

[BibT_eX]

[DOI]

Hao Yuan

Shuiwang Ji

Proceedings of the 8th International Conference on Learning Representations, 2020

Context-aware Deep Representation Learning for Geo-spatiotemporal Analysis.

[BibT_eX]

[DOI]

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019

Global Transformer U-Nets for Label-Free Prediction of Fluorescence Images.

[BibT_eX]

[DOI]

CoRR, 2019

Computational modeling of cellular structures using conditional deep generative networks.

[BibT_eX]

[DOI]

Bioinform., 2019

XFake: Explainable Fake News Detector with Visualizations.

[BibT_eX]

[DOI]

Proceedings of the World Wide Web Conference, 2019

Spatial Variational Auto-Encoding via Matrix-Variate Normal Distributions.

[BibT_eX]

[DOI]

Zhengyang Wang

Hao Yuan

Shuiwang Ji

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Learning Hierarchical and Shared Features for Improving 3D Neuron Reconstruction.

[BibT_eX]

[DOI]

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Learning Local and Global Multi-context Representations for Document Classification.

[BibT_eX]

[DOI]

Yi Liu

Hao Yuan

Shuiwang Ji

Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

Interpreting Deep Models for Text Analysis via Optimization and Regularization Methods.

[BibT_eX]

[DOI]

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

2017

Pixel Deconvolutional Networks.

[BibT_eX]

[DOI]

CoRR, 2017

Hao Yuan

Timeline

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