Zijian Li

Orcid: 0000-0002-3964-3789

Affiliations:

Guangdong University of Technology, Guangzhou, China

According to our database¹, Zijian Li authored at least 37 papers between 2017 and 2025.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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Article

PhD thesis

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Bibliography

2025

Unifying invariant and variant features for graph out-of-distribution via probability of necessity and sufficiency.

[BibT_eX]

[DOI]

Neural Networks, 2025

2024

Motif Graph Neural Network.

[BibT_eX]

[DOI]

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

Graph Domain Adaptation: A Generative View.

[BibT_eX]

[DOI]

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

Transferable Time-Series Forecasting Under Causal Conditional Shift.

[BibT_eX]

[DOI]

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

TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations.

[BibT_eX]

[DOI]

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

Time-series domain adaptation via sparse associative structure alignment: Learning invariance and variance.

[BibT_eX]

[DOI]

Neural Networks, 2024

Causal Representation Learning from Multimodal Biological Observations.

[BibT_eX]

[DOI]

CoRR, 2024

Causal Temporal Representation Learning with Nonstationary Sparse Transition.

[BibT_eX]

[DOI]

CoRR, 2024

Learning Discrete Latent Variable Structures with Tensor Rank Conditions.

[BibT_eX]

[DOI]

CoRR, 2024

From Orthogonality to Dependency: Learning Disentangled Representation for Multi-Modal Time-Series Sensing Signals.

[BibT_eX]

[DOI]

CoRR, 2024

On the Identification of Temporally Causal Representation with Instantaneous Dependence.

[BibT_eX]

[DOI]

CoRR, 2024

Debiased Model-based Interactive Recommendation.

[BibT_eX]

[DOI]

CoRR, 2024

When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting.

[BibT_eX]

[DOI]

CoRR, 2024

Unifying Invariance and Spuriousity for Graph Out-of-Distribution via Probability of Necessity and Sufficiency.

[BibT_eX]

[DOI]

CoRR, 2024

Individual Causal Structure Learning from Population Data.

[BibT_eX]

[DOI]

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

Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning.

[BibT_eX]

[DOI]

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

Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation.

[BibT_eX]

[DOI]

José Miguel Hernández-Lobato

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

LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

TNPAR: Topological Neural Poisson Auto-Regressive Model for Learning Granger Causal Structure from Event Sequences.

[BibT_eX]

[DOI]

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

2023

Identifying Semantic Component for Robust Molecular Property Prediction.

[BibT_eX]

[DOI]

CoRR, 2023

Subspace Identification for Multi-Source Domain Adaptation.

[BibT_eX]

[DOI]

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

2022

Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance.

[BibT_eX]

[DOI]

CoRR, 2022

REST: Debiased Social Recommendation via Reconstructing Exposure Strategies.

[BibT_eX]

[DOI]

CoRR, 2022

2021

Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems.

[BibT_eX]

[DOI]

ACM Trans. Intell. Syst. Technol., 2021

Semi-supervised disentangled framework for transferable named entity recognition.

[BibT_eX]

[DOI]

Neural Networks, 2021

TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations.

[BibT_eX]

[DOI]

CoRR, 2021

Transferable Time-Series Forecasting under Causal Conditional Shift.

[BibT_eX]

[DOI]

CoRR, 2021

Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?

[BibT_eX]

[DOI]

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

Aggregating From Multiple Target-Shifted Sources.

[BibT_eX]

[DOI]

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

Time Series Domain Adaptation via Sparse Associative Structure Alignment.

[BibT_eX]

[DOI]

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

2020

TAG : Type Auxiliary Guiding for Code Comment Generation.

[BibT_eX]

[DOI]

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Disentanglement Challenge: From Regularization to Reconstruction.

[BibT_eX]

[DOI]

CoRR, 2019

Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems.

[BibT_eX]

[DOI]

CoRR, 2019

NADAQ: Natural Language Database Querying Based on Deep Learning.

[BibT_eX]

[DOI]

IEEE Access, 2019

Learning Disentangled Semantic Representation for Domain Adaptation.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

An Encoder-Decoder Framework Translating Natural Language to Database Queries.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

2017

An Encoder-Decoder Framework Translating Natural Language to Database Queries.

[BibT_eX]

[DOI]

CoRR, 2017

Zijian Li

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