Personal profile
Biography
I am a Research Fellow at the Australian National University, working with Prof Stephen Gould. My current research focuses are 3D Content Modeling and Out-of-Distribution Generalization. Previously, I was a PhD student at the Australian National University, where I worked on model generalization prediction. My resume is available at CV.
Qualifications
PhD in Computer Science
Research Interests
- Machine Learning Safety: Concentrated on the safety of large language models and multimodal models, with a focus on improving resilience and reliability. Emphasis is placed on developing robust models for varied environments and creating monitoring mechanisms to detect misuse and analyze failure patterns.
- 3D Content Modeling & Generation: Focused on the advancement of 3D modeling and generation, specifically for refractive objects. By applying optical principles, it aims to significantly enhance the realism and accuracy of 3D objects and scenes.
PhD Research Topic: Model Generalization Prediction. The primary focus lies in the accurate prediction of model generalization across diverse testing environments without relying on human annotations. The significance of this investigation lies in its potential to identify and diagnose potential failure cases, while also providing valuable guidance for future model training endeavors.
Please check my personal website for my research works: https://weijiandeng.xyz/
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Collaborations and top research areas from the last five years
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An Empirical Study Into What Matters for Calibrating Vision–Language Models
Tu, W., Deng, W., Campbell, D., Gould, S. & Gedeon, T., 2024, In: Proceedings of Machine Learning Research. 235, p. 48791-48808 18 p.Research output: Contribution to journal › Conference article › peer-review
2 Citations (Scopus) -
Differentiable Neural Surface Refinement for Modeling Transparent Objects
Deng, W., Campbell, D., Sun, C., Kanitkar, S., Shaffer, M. E. & Gould, S., 2024, Proceedings - 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024. IEEE Computer Society, p. 20268-20277 10 p. (Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review
6 Citations (Scopus) -
Ray Deformation Networks for Novel View Synthesis of Refractive Objects
Deng, W., Campbell, D., Sun, C., Kanitkar, S., Shaffer, M. & Gould, S., 2024, Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024. Institute of Electrical and Electronics Engineers Inc., p. 3106-3116 11 p. (Proceedings - 2024 IEEE Winter Conference on Applications of Computer Vision, WACV 2024).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › peer-review
7 Citations (Scopus) -
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions?
Tu, W., Deng, W., Zheng, L. & Gedeon, T., 2024, In: Transactions on Machine Learning Research. 2024Research output: Contribution to journal › Article › peer-review
1 Citation (Scopus) -
Rethinking Triplet Loss for Domain Adaptation
Deng, W., Zheng, L., Sun, Y. & Jiao, J., Jan 2021, In: IEEE Transactions on Circuits and Systems for Video Technology. 31, 1, p. 29-37 9 p., 8964455.Research output: Contribution to journal › Article › peer-review
80 Citations (Scopus)