Posts by Collection

Causal Discovery with Mixed Linear and Nonlinear Additive Noise Models: A Scalable Approach

Published in CLeaR, 2024

This paper proposes a causal discovery algorithm that identifies edge directions beyond Markov equivalence classes using the Jacobian of the score function, suitable for mixed linear and nonlinear mechanisms.

Recommended citation: Wenqin Liu, Biwei Huang, Erdun Gao, Qiuhong Ke, Howard Bondell, Mingming Gong. "Causal Discovery with Mixed Linear and Nonlinear Additive Noise Models: A Scalable Approach." CLeaR 2024.
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A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery

Published in ICLR, 2025

SkewScore introduces a skewness-based criterion to distinguish causal from anti-causal directions in models with heteroscedastic symmetric noise, and shows strong empirical and theoretical performance.

Recommended citation: Yingyu Lin*, Yuxing Huang*, Wenqin Liu*, Haoran Deng*, Ignavier Ng, Kun Zhang, Mingming Gong, Yi-An Ma, Biwei Huang. "A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery." ICLR 2025.
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MissScore: High-Order Score Estimation in the Presence of Missing Data

Published in ICML, 2025

MissScore is a novel algorithm that enables causal discovery with incomplete datasets by leveraging high-order score function estimation, achieving state-of-the-art results in simulations.

Recommended citation: Wenqin Liu, Haonan Hou, Erdun Gao, Biwei Huang, Qiuhong Ke, Howard Bondell, Mingming Gong. "MissScore: High-Order Score Estimation in the Presence of Missing Data." ICML 2025.
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Introduction to Machine Learning (COMP90049) Permalink

Teaching Assistant (2023), The University of Melbourne, 2023

Introduces graduate-level machine learning from a mathematical perspective, covering algorithms, model evaluation, and real-world applications.

Machine Learning (COMP30027) Permalink

Teaching Assistant (2024), The University of Melbourne, 2024

Introduces undergraduate-level machine learning, including foundational concepts, core algorithms, and applications across domains.

Statistical Modelling for Data Science (MAST90139) Permalink

Teaching Assistant (2023,2024), The University of Melbourne, 2024

Introduces statistical models including GLMs, mixed models, and non-parametric regression, with emphasis on causal inference and missing data techniques in data science.

Data and Decision Making (MAST90072) Permalink

Teaching Assistant (2023,2024,2025), The University of Melbourne, 2025

Introduces the process of data collection, statistical analysis, and decision-making, with a focus on biotechnology and effective communication of results.