Mingzhou Liu

Orcid: 0000-0002-0297-0938

Affiliations:
  • Peking University, Department of Computer Science and Technology, Beijing, China
  • Shanghai Jiao Tong University, Department of Electronic Engineering, China (former)


According to our database1, Mingzhou Liu authored at least 12 papers between 2019 and 2025.

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

Timeline

Legend:

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Article 
PhD thesis 
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Links

Online presence:

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Bibliography

2025
Conditional Local Independence Testing for Dynamic Causal Discovery.
CoRR, June, 2025

Learning Causal Alignment for Reliable Disease Diagnosis.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Bayesian Intervention Optimization for Causal Discovery.
CoRR, 2024

Causal Discovery via Conditional Independence Testing with Proxy Variables.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
Exploring Counterfactual Alignment Loss towards Human-centered AI.
CoRR, 2023

Causal Discovery with Unobserved Variables: A Proxy Variable Approach.
CoRR, 2023

Causal Discovery from Subsampled Time Series with Proxy Variables.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Which Invariance Should We Transfer? A Causal Minimax Learning Approach.
Proceedings of the International Conference on Machine Learning, 2023

2021
Context-LGM: Leveraging Object-Context Relation for Context-Aware Object Recognition.
CoRR, 2021

CA-Net: Leveraging Contextual Features for Lung Cancer Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021

2020
Adaptive lossless compression of skeleton sequences.
Signal Process. Image Commun., 2020

2019
A Multimodal Lossless Coding Method for Skeletons in Videos.
Proceedings of the IEEE International Conference on Multimedia & Expo Workshops, 2019


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