List of Publications
Selected publications are underlined.
* First author † Co-first author ✉ Corresponding author
- Under Submission
- Qi Chen*✉, Fabio Ramos, Alan Aspuru-Guzik, Florian Shkurti✉. [Informing Acquisition Functions via Foundation Models for Molecular Discovery, 2025.]
- Doudou Zhang, Qi Chen✉. Constrained Look-ahead Guidance for Interference-Aware Flow Editing.
- Xing Shen, Yifan Qin, Gezheng Xu, Qi Chen, Changjian Shui. Position: Dataset Misuse Risk Evaluation Requires Operationalizing the Burden of Proof.
- Thesis (Excellent, placed on Honor List)
- Meta Learning, Continual Learning
- Qi Chen*✉, Changjian Shui, Ligong Han, and Mario Marchand✉. On the Stability-Plasticity Dilemma in Continual Meta-Learning: Theory and Algorithm. NeurIPS 2023.[Open Review] [Paper] [Code]
- Qi Chen*✉, Changjian Shui, Mario Marchand✉. Generalization Bounds for Meta-Learning: An Information-Theoretic Analysis. NeurIPS 2021. (Spotlight, 3% of submissions) [Open Review][Paper] [Code]
- Generative Models
- Qi Chen*✉, Jerry Zhu, Florian Shkurti✉. Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis. ICLR 2025.[Open Review] [Paper] [Code]
- Ligong Han, Song Wen, Qi Chen, Zhixing Zhang, Kunpeng Song, Mengwei Ren, et al. Proxedit: Improving tuning-free real image editing with proximal guidance. WACV 2024.
- Domain Adaptation
- Gezheng Xu, Qi Chen, Qiuhao Zeng, Charles Ling, Boyu Wang. Discretized Density-Guided Source-Free Adaptation for Continuous Targets. ICML 2026.(Spotlight, 2.2% of submissions)
- Qi Chen*, and Mario Marchand✉. Algorithm-Dependent Bounds for Representation Learning of Multi-Source Domain Adaptation. AISTATS 2023.[Paper] [Code]
- Changjian Shui, Qi Chen, Jun Wen, Fan Zhou, Christian Gagné, and Boyu Wang. A novel domain adaptation theory with Jensen–Shannon divergence. Knowledge-Based Systems, 2022.[Paper]
- Changjian Shui, Qi Chen, Jun Wen, Fan Zhou, Christian Gagné, and Boyu Wang. Beyond H-divergence: Domain Adaptation Theory with Jensen-Shannon Divergence. 2020. [paper]
- Algorithmic Fairness
- Gezheng Xu, Qi Chen, Charles Ling, Boyu Wang, Changjian Shui. Intersectional Unfairness Discovery. ICML 2024.
- Changjian Shui†, Gezheng Xu†, Qi Chen, Jiaqi Li, Charles X. Ling, Tal Arbel, Boyu Wang, and Christian Gagné. On learning fairness and accuracy on multiple subgroups. NeurIPS 2022.[Paper]
- Changjian Shui, Qi Chen, Jiaqi Li, Boyu Wang, and Christian Gagné. Fair Representation Learning through Implicit Path Alignment. ICML 2022. [Paper]
- Sequence Prediction
- Qiuhao Zeng, Longkai Huang, Qi Chen, Charles Ling, Boyu Wang. Towards Understanding Evolving Patterns in Sequential Data. NeurIPS 2024.
