- Erdun Gao, Liang Zhang, Jake Fawkes, Aoqi Zuo, Wenqin Liu, Haoxuan Li, Mingming Gong, Dino Sejdinovic. Observationally Informed Adaptive Causal Experimental Design. ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD), Oral, 2026.
- Wenkang Jiang, Yuhang Liu, Erdun Gao, Ehsan Abbasnejad, Lina Yao, Javen Qinfeng Shi. Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction. ACM SIGKDD Conference On Knowledge Discovery and Data Mining (KDD), 2026.
- Erdun Gao, Jake Fawkes, Dino Sejdinovic. Causal-EPIG: Causally Aligned Active CATE Estimation. International Conference on Machine Learning (ICML), 2026.
- Wenqin Liu, Weizhi Quan, Aoqi Zuo, Erdun Gao†, Vu Nguyen, Dino Sejdinovic, Howard Bondell, Mingming Gong. TimeLAVA: Learning-Agnostic Valuation for Time Series Data. International Conference on Machine Learning (ICML), 2026.
- Haoxiang Wang, Aoqi Zuo, Ziyan Wang, Zhiheng Zhang, Erdun Gao, Kun Zhang, Haoxuan Li, Mingming Gong. Treatment Responder Classification with Abstention. International Conference on Machine Learning (ICML), Spotlight, 2026.
- Wenkang Jiang, Yuhang Liu, Yichao Cai, Erdun Gao, Jiayi Dong, Ehsan Abbasnejad, Lina Yao, Javen Qinfeng Shi. What Makes a Good Representation for Single-Cell Perturbation Prediction? International Conference on Machine Learning (ICML), 2026.
- Erdun Gao, Dino Sejdinovic. ActiveCQ: Active Estimation of Causal Quantities. International Conference on Learning Representations (ICLR), 2026.
- Yuhang Liu, Zhen Zhang, Dong Gong, Erdun Gao, Biwei Huang, Mingming Gong, Anton van den Hengel, Kun Zhang, Javen Qinfeng Shi. Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning. International Conference on Learning Representations (ICLR), 2026.
- Yuhang Liu, Dong Gong, Yichao Cai, Erdun Gao, Zhen Zhang, Biwei Huang, Mingming Gong, Anton van den Hengel, Javen Qinfeng Shi. I Predict Therefore I Am: Is Next Token Prediction Enough to Learn Human-Interpretable Concepts from Data? International Conference on Learning Representations (ICLR), 2026.
- Erdun Gao, Howard Bondell, Shaoli Huang, Mingming Gong. Domain Generalization via Content Factors Isolation: A Two-level Latent Variable Modeling Approach. Machine Learning (MLJ), 2025.
- Wenqin Liu, Haoze Hou, Erdun Gao, Biwei Huang, Qiuhong Ke, Howard Bondell, Mingming Gong. MissScore: High-Order Score Estimation in the Presence of Missing Data. International Conference on Machine Learning (ICML), 2025.
- Xinshu Li, Ruoyu Wang, Erdun Gao, Mingming Gong, Lina Yao. Causality-aligned Prompt Learning via Diffusion-based Counterfactual Generation. ACM International Conference on Multimedia (ACM MM), 2025.
- Zuopeng Yang, Jiluan Fan, Anli Yan, Erdun Gao, Xin Lin, Tao Li, Kanghua Mo, Changyu Dong. Distraction is All You Need for Multimodal Large Language Model Jailbreaking. IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Highlight, 2025.
- Yichao Cai, Yuhang Liu, Erdun Gao, Tianjiao Jiang, Zhen Zhang, Javen Qinfeng Shi. On the Value of Cross-Modal Misalignment in Multimodal Representation Learning. Advances in Neural Information Processing Systems (NeurIPS), Spotlight, 2025.
- Erdun Gao, Howard Bondell, Wei Huang, Mingming Gong. A Variational Framework for Estimating the Treatment Effects with Measurement Error. International Conference on Learning Representations (ICLR), 2024.
- 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. Conference on Causal Learning and Reasoning (CLeaR), 2024.
- Erdun Gao, Junjia Chen, Li Shen, Tongliang Liu, Mingming Gong, Howard Bondell. FedDAG: Federated DAG Structure Learning. Transactions on Machine Learning Research (TMLR), 2023.
- Zuopeng Yang, Tianshu Chu, Xin Lin, Erdun Gao, Daqing Liu, Jie Yang, Chaoyue Wang. Eliminating Contextual Prior Bias for Semantic Image Editing via Dual-Cycle Diffusion. IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT), 2023.
- Xiaoran Zhang, Zhibin Pan, Quan Zhou, Erdun Gao, Xinyi Gao, Guojun Fan. A novel two-level embedding pattern for grayscale-invariant reversible data hiding. Multimedia Tools and Applications (MTA), 2023.
- Erdun Gao, Ignavier Ng, Mingming Gong, Li Shen, Wei Huang, Tongliang Liu, Kun Zhang, Howard Bondell. MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. Advances in Neural Information Processing Systems (NeurIPS), 2022.
- Guojun Fan, Zhibin Pan, Erdun Gao, Xinyi Gao, Xiaoran Zhang. Reversible data hiding method based on combining IPVO with bias-added Rhombus predictor by multi-predictor mechanism. Signal Processing (SP), 2021.
- Xinyi Gao, Zhibin Pan, Erdun Gao, Guojun Fan. Reversible data hiding for high dynamic range images using two-dimensional prediction-error histogram of the second time prediction. Signal Processing (SP), 2020.
- Zhibin Pan, Xinyi Gao, Erdun Gao, Guojun Fan. Adaptive complexity for pixel-value-ordering based reversible data hiding. IEEE Signal Processing Letters (SPL), 2020.
- Zhibin Pan, Xinyi Gao, Lingfei Wang, Erdun Gao. Effective reversible data hiding using dynamic neighboring pixels prediction based on prediction-error histogram. Multimedia Tools and Applications (MTA), 2020.
- Erdun Gao, Zhibin Pan, Xinyi Gao. Reversible data hiding based on novel pairwise PVO and annular merging strategy. Information Sciences (INS), 2019.
- Zhibin Pan, Erdun Gao, Ruoxin Zhu, Lingfei Wang. A low bit-rate SOC-based reversible data hiding algorithm by using new encoding strategies. Multimedia Tools and Applications (MTA), 2019.
- Zhibin Pan, Erdun Gao. Reversible data hiding based on novel embedding structure PVO and adaptive block-merging strategy. Multimedia Tools and Applications (MTA), 2019.