About me
I am a PhD student in the Department of Computing at Imperial College London, learning to train energy-based models under the supervision of Yingzhen Li. I completed my undergraduate studies in the School of Computer Science and Engineering at Sun Yat-sen University and previously worked as a research intern at Apple MLR, Shell AI, Tencent AI Lab, and Tencent Jarvis Lab.
Publications
* denotes equal contribution; check the full list here
Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching
Oral (Accept rate~1.8%)
Zijing Ou*, Mingtian Zhang*, Andi Zhang, Tim Xiao, Yingzhen Li, and David Barber. International Conference on Learning Representations (ICLR), 2025. [paper] [code]Energy-Based Modelling for Discrete and Mixed Data via Heat Equations on Structured Spaces
Tobias Schröder*, Zijing Ou*, Yingzhen Li, and Andrew Duncan. Neural Processing Information Systems (NeurIPS), 2024. [paper] [code]Energy Discrepancies: A Score-Independent Loss for Energy-Based Models
Tobias Schröder, Zijing Ou, Jen Ning Lim, Yingzhen Li, Sebastian Vollmer, and Andrew Duncan. Neural Processing Information Systems (NeurIPS), 2023. [paper] [code]Learning Neural Set Functions Under the Optimal Subset Oracle
Oral (Accept rate~1.7%)
Zijing Ou, Tingyang Xu, Qinliang Su, Yingzhen Li, Peilin Zhao, and Yatao Bian. Neural Processing Information Systems (NeurIPS), 2022. [paper] [code] [slides] [poster]
![[poster]](https://nips.cc/media/PosterPDFs/NeurIPS%202022/54333.png?t=1669298430.3968306){kind=link}
Services
- Conference Reviewing: ICLR (2024-2025), ICML (2022-2024), NeurIPS (2022-2024), AISTAT (2023-2025), IJCAI (2022-2024), ACL (2022), NAACL (2022)