Mr Erdun Gao
Grant-Funded Researcher (B)
School of Mathematical Sciences
College of Science
Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.
| Date | Position | Institution name |
|---|---|---|
| 2024 - ongoing | Researcher | University of Adelaide |
| Year | Citation |
|---|---|
| 2025 | Gao, E., Bondell, H., Huang, S., & Gong, M. (2025). Domain generalization via content factors isolation: a two-level latent variable modeling approach. Machine Learning, 114(4), 88-1-88-33. |
| 2024 | Yang, Z., Chu, T., Lin, X., Gao, E., Liu, D., Yang, J., & Wang, C. (2024). Eliminating Contextual Prior Bias for Semantic Image Editing via Dual-Cycle Diffusion. IEEE Transactions on Circuits and Systems for Video Technology, 34(2), 1316-1320. Scopus27 WoS24 |
| 2023 | Gao, E., Chen, J., Shen, L., Liu, T., Gong, M., & Bondell, H. (2023). FedDAG: Federated DAG Structure Learning. Transactions on Machine Learning Research, 2023-January, 1-36. Scopus15 |
| 2023 | Zhang, X., Pan, Z., Zhou, Q., Gao, E., Gao, X., & Fan, G. (2023). A novel two-level embedding pattern for grayscale-invariant reversible data hiding. Multimedia Tools and Applications, 82(22), 33911-33935. Scopus3 |
| 2021 | Fan, G., Pan, Z., Gao, E., Gao, X., & Zhang, X. (2021). Reversible data hiding method based on combining IPVO with bias-added Rhombus predictor by multi-predictor mechanism. Signal Processing, 180, 107888. Scopus29 |
| 2020 | Gao, X., Pan, Z., Gao, E., & Fan, G. (2020). Reversible data hiding for high dynamic range images using two-dimensional prediction-error histogram of the second time prediction. Signal Processing, 173, 107579. Scopus51 |
| 2020 | Pan, Z., Gao, X., Wang, L., & Gao, E. (2020). Effective reversible data hiding using dynamic neighboring pixels prediction based on prediction-error histogram. Multimedia Tools and Applications, 79(17-18), 12569-12595. Scopus13 |
| 2020 | Pan, Z., Gao, X., Gao, E., & Fan, G. (2020). Adaptive Complexity for Pixel-Value-Ordering Based Reversible Data Hiding. IEEE SIGNAL PROCESSING LETTERS, 27, 915-919. Scopus42 WoS34 |
| 2019 | Gao, E., Pan, Z., & Gao, X. (2019). Reversible data hiding based on novel pairwise PVO and annular merging strategy. Information Sciences, 505, 549-561. Scopus32 |
| 2019 | Pan, Z., & Gao, E. (2019). Reversible data hiding based on novel embedding structure PVO and adaptive block-merging strategy. Multimedia Tools and Applications, 78(18), 26047-26071. Scopus14 |
| 2019 | Pan, Z., Gao, E., Zhu, R., & Wang, L. (2019). A low bit-rate SOC-based reversible data hiding algorithm by using new encoding strategies. Multimedia Tools and Applications, 78(15), 21223-21244. Scopus2 |
| Year | Citation |
|---|---|
| 2025 | Yang, Z., Fan, J., Yan, A., Gao, E., Lin, X., Li, T., . . . Dong, C. (2025). Distraction is All You Need for Multimodal Large Language Model Jailbreaking. In 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (pp. 9467-9476). IEEE. DOI |
| 2025 | Li, X., Wang, R., Gao, E., Gong, M., & Yao, L. (2025). Causality-aligned Prompt Learning via Diffusion-based Counterfactual Generation. In Mm 2025 Proceedings of the 33rd ACM International Conference on Multimedia Co Located with mm 2025 (pp. 5208-5217). ACM. DOI |
| 2025 | Liu, W., Hou, H., Gao, E., Huang, B., Ke, Q., Bondell, H., & Gong, M. (2025). MissScore: High-Order Score Estimation in the Presence of Missing Data. In Proceedings of Machine Learning Research Vol. 267 (pp. 38664-38691). |
| 2024 | Gao, E., Bondell, H., Huang, W., & Gong, M. (2024). A VARIATIONAL FRAMEWORK FOR ESTIMATING CONTINUOUS TREATMENT EFFECTS WITH MEASUREMENT ERROR. In 12th International Conference on Learning Representations, ICLR 2024. Online: International Conference on Learning Representations, ICLR. Scopus2 |
| 2024 | Liu, W., Huang, B., Gao, E., Ke, Q., Bondell, H., & Gong, M. (2024). Causal Discovery with Mixed Linear and Nonlinear Additive Noise Models: A Scalable Approach. In Proceedings of Machine Learning Research Vol. 236 (pp. 1237-1263). Online: ML Research Press. Scopus5 |
| 2022 | Gao, E., Ng, I., Gong, M., Shen, L., Huang, W., Liu, T., . . . Bondell, H. (2022). MissDAG: Causal Discovery in the Presence of Missing Data with Continuous Additive Noise Models. In Advances in Neural Information Processing Systems Vol. 35. Online: Neural information processing systems foundation. Scopus21 |
| Date | Role | Research Topic | Program | Degree Type | Student Load | Student Name |
|---|---|---|---|---|---|---|
| 2025 | Co-Supervisor | Function Space Variational Deep Learning | Master of Philosophy | Master | Full Time | Mr Rahul Tejeshwa |
| 2025 | Co-Supervisor | Function Space Variational Deep Learning | Master of Philosophy | Master | Full Time | Mr Rahul Tejeshwa |
Connect With Me
External Profiles
