Zijian Li
Orcid: 0000-0002-3964-3789Affiliations:
- Guangdong University of Technology, Guangzhou, China
According to our database1,
Zijian Li
authored at least 54 papers
between 2017 and 2025.
Collaborative distances:
Collaborative distances:
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Bibliography
2025
Should Bias Always be Eliminated? A Principled Framework to Use Data Bias for OOD Generation.
CoRR, July, 2025
Causal View of Time Series Imputation: Some Identification Results on Missing Mechanism.
CoRR, May, 2025
Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning.
CoRR, May, 2025
CoRR, February, 2025
Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting.
CoRR, February, 2025
Leveraging Constrained Monte Carlo Tree Search to Generate Reliable Long Chain-of-Thought for Mathematical Reasoning.
CoRR, February, 2025
Identification of Nonparametric Dynamic Causal Structure and Latent Process in Climate System.
CoRR, January, 2025
Unifying invariant and variant features for graph out-of-distribution via probability of necessity and sufficiency.
Neural Networks, 2025
StateHPs: State Hawkes processes for Granger causal discovery from non-stationary event sequences.
Inf. Sci., 2025
Temporal latent variable structural causal model for causal discovery under external interferences.
Neurocomputing, 2025
Interpretable high-order knowledge graph neural network for predicting synthetic lethality in human cancers.
Briefings Bioinform., 2025
Proceedings of the ACM on Web Conference 2025, 2025
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
On the Identification of Temporal Causal Representation with Instantaneous Dependence.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025
Disentangling Long-Short Term State Under Unknown Interventions for Online Time Series Forecasting.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025
2024
ACM Trans. Knowl. Discov. Data, April, 2024
IEEE Trans. Pattern Anal. Mach. Intell., April, 2024
IEEE Trans. Neural Networks Learn. Syst., February, 2024
Time-series domain adaptation via sparse associative structure alignment: Learning invariance and variance.
Neural Networks, 2024
From Orthogonality to Dependency: Learning Disentangled Representation for Multi-Modal Time-Series Sensing Signals.
CoRR, 2024
On the Identification of Temporally Causal Representation with Instantaneous Dependence.
CoRR, 2024
When and How: Learning Identifiable Latent States for Nonstationary Time Series Forecasting.
CoRR, 2024
Unifying Invariance and Spuriousity for Graph Out-of-Distribution via Probability of Necessity and Sufficiency.
CoRR, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning.
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.
Proceedings of the Forty-first International Conference on Machine Learning, 2024
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.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024
2023
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.
CoRR, 2022
CoRR, 2022
2021
Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems.
ACM Trans. Intell. Syst. Technol., 2021
Neural Networks, 2021
CoRR, 2021
Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
Proceedings of the 38th International Conference on Machine Learning, 2021
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020
2019
Causal Mechanism Transfer Network for Time Series Domain Adaptation in Mechanical Systems.
CoRR, 2019
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019
2018
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018
2017
CoRR, 2017