Haoyang Li

Orcid: 0000-0003-3544-5563

Affiliations:

Tsinghua University, Department of Computer Science and Technology, Beijing, China

According to our database¹, Haoyang Li authored at least 33 papers between 2018 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

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In proceedings

Article

PhD thesis

Dataset

Other

Bibliography

2025

Federated Causal Inference in Healthcare: Methods, Challenges, and Applications.

[BibT_eX]

[DOI]

CoRR, May, 2025

Modular Machine Learning: An Indispensable Path towards New-Generation Large Language Models.

[BibT_eX]

[DOI]

CoRR, April, 2025

Disentangled Dynamic Graph Attention Network for Out-of-Distribution Sequential Recommendation.

[BibT_eX]

[DOI]

ACM Trans. Inf. Syst., January, 2025

COLA-GLM: collaborative one-shot and lossless algorithms of generalized linear models for decentralized observational healthcare data.

[BibT_eX]

[DOI]

npj Digit. Medicine, 2025

Federated target trial emulation using distributed observational data for treatment effect estimation.

[BibT_eX]

[DOI]

npj Digit. Medicine, 2025

Graph Machine Learning under Distribution Shifts: Adaptation, Generalization and Extension to LLM.

[BibT_eX]

[DOI]

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

2024

Invariant Node Representation Learning under Distribution Shifts with Multiple Latent Environments.

[BibT_eX]

[DOI]

ACM Trans. Inf. Syst., January, 2024

Identification of Parkinson's disease PACE subtypes and repurposing treatments through integrative analyses of multimodal data.

[BibT_eX]

[DOI]

npj Digit. Medicine, 2024

Cross-Space Adaptive Filter: Integrating Graph Topology and Node Attributes for Alleviating the Over-smoothing Problem.

[BibT_eX]

[DOI]

Proceedings of the ACM on Web Conference 2024, 2024

LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs?

[BibT_eX]

[DOI]

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

CurBench: Curriculum Learning Benchmark.

[BibT_eX]

[DOI]

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

Disentangled Graph Self-supervised Learning for Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

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

OOD-GNN: Out-of-Distribution Generalized Graph Neural Network: (Extended Abstract).

[BibT_eX]

[DOI]

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Multimodal Graph Neural Architecture Search under Distribution Shifts.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Disentangled Graph Contrastive Learning With Independence Promotion.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., August, 2023

OOD-GNN: Out-of-Distribution Generalized Graph Neural Network.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., July, 2023

Out-of-Distribution Generalized Dynamic Graph Neural Network with Disentangled Intervention and Invariance Promotion.

[BibT_eX]

[DOI]

CoRR, 2023

LLM4DyG: Can Large Language Models Solve Problems on Dynamic Graphs?

[BibT_eX]

[DOI]

CoRR, 2023

Large Graph Models: A Perspective.

[BibT_eX]

[DOI]

CoRR, 2023

Tutorials at The Web Conference 2023.

[BibT_eX]

[DOI]

Krishnaram Kenthapadi

Behrooz Omidvar-Tehrani

Proceedings of the Companion Proceedings of the ACM Web Conference 2023, 2023

Spectral Invariant Learning for Dynamic Graphs under Distribution Shifts.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Multimedia Cognition and Evaluation in Open Environments.

[BibT_eX]

[DOI]

Proceedings of the 1st International Workshop on Multimedia Content Generation and Evaluation: New Methods and Practice, 2023

Curriculum Graph Machine Learning: A Survey.

[BibT_eX]

[DOI]

Haoyang Li

Xin Wang

Wenwu Zhu

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

AutoGT: Automated Graph Transformer Architecture Search.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Intention-aware Sequential Recommendation with Structured Intent Transition : (Extended Abstract).

[BibT_eX]

[DOI]

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

2022

Intention-Aware Sequential Recommendation With Structured Intent Transition.

[BibT_eX]

[DOI]

IEEE Trans. Knowl. Data Eng., 2022

Out-Of-Distribution Generalization on Graphs: A Survey.

[BibT_eX]

[DOI]

CoRR, 2022

Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Learning Invariant Graph Representations for Out-of-Distribution Generalization.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

AutoGL: A Library for Automated Graph Learning.

[BibT_eX]

[DOI]

CoRR, 2021

Disentangled Contrastive Learning on Graphs.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2019

Fates of Microscopic Social Ecosystems: Keep Alive or Dead?

[BibT_eX]

[DOI]

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

2018

Billion-Scale Network Embedding with Iterative Random Projection.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Data Mining, 2018

Haoyang Li

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