@article{chen2026edival,title={EdiVal-Agent: An Object-Centric Framework for Automated, Scalable, Fine-Grained Evaluation of Multi-Turn Editing},author={Chen, Tianyu and Zhang, Yasi and Zhang, Zhi and Yu, Peiyu and Wang, Shu and Wang, Zhendong and Lin, Kevin and Wang, Xiaofei and Yang, Zhengyuan and Li, Linjie and Lin, Chung-Ching and Xie, Jianwen and Leong, Oscar and Wang, Lijuan and Wu, Ying Nian and Zhou, Mingyuan},journal={The 14th International Conference on Learning Representations},year={2026},media={https://mp.weixin.qq.com/s/jlVDWl7wJ8SGFcGdRG7wGA},tldr={An object-centric VLM agent that automates fine-grained, multi-turn image-editing evaluation, eliminating reliance on human annotators.}}
ICLR 2026
Score Distillation Beyond Acceleration: Generative Modeling from Corrupted Data
Tianyu Chen*, Yasi Zhang*, Zhendong Wang, and 2 more authors
The 14th International Conference on Learning Representations, 2026
@article{chen2026scoredistillation,title={Score Distillation Beyond Acceleration: Generative Modeling from Corrupted Data},author={Chen, Tianyu and Zhang, Yasi and Wang, Zhendong and Wu, Ying Nian and Zhou, Mingyuan},journal={The 14th International Conference on Learning Representations},year={2026},tldr={Score distillation is not merely an acceleration technique — it enhances generation quality from corrupted data, both empirically and theoretically.}}
2025
Preprint
Restoration score distillation: From corrupted diffusion pretraining to one-step high-quality generation
Yasi Zhang*, Tianyu Chen*, Zhendong Wang, and 3 more authors
@article{zhang2025restoration,title={Restoration score distillation: From corrupted diffusion pretraining to one-step high-quality generation},author={Zhang, Yasi and Chen, Tianyu and Wang, Zhendong and Wu, Ying Nian and Zhou, Mingyuan and Leong, Oscar},journal={arXiv preprint arXiv:2505.13377},year={2025},}
Preprint
A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation
@article{chen2026causal,title={A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation},author={Chen, Tianyu and Song, Xinran and Zhou, Mingyuan},journal={Preprint.},year={2025},}
NeurIPS 2025
Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
Yifan Sun, Jingyan Shen, Yibin Wang, and 4 more authors
Advances in Neural Information Processing Systems 2025, 2025
@article{sun2025improving,title={Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay},author={Sun, Yifan and Shen, Jingyan and Wang, Yibin and Chen, Tianyu and Wang, Zhendong and Zhou, Mingyuan and Zhang, Huan},journal={Advances in Neural Information Processing Systems 2025},year={2025},}
NeurIPS 2025
CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates
Tianyu Chen, Vansh Bansal, and James G. Scott
Advances in Neural Information Processing Systems 2025, 2025
@article{chen2025colt,title={CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates},author={Chen, Tianyu and Bansal, Vansh and Scott, James G.},journal={Advances in Neural Information Processing Systems 2025},year={2025},tldr={A principled conditional localization test for validating neural posterior estimators. NeurIPS 2025 Spotlight.}}
Preprint
The surprising strength of weak classifiers for validating neural posterior estimates
@article{chen2025weakclassifiers,title={The surprising strength of weak classifiers for validating neural posterior estimates},author={Chen, Tianyu and Bansal, Vansh and Scott, James G.},journal={Preprint.},year={2025},}
AISTATS 2025
Conditional diffusions for amortized neural posterior estimation
Tianyu Chen, Vansh Bansal, and James G. Scott
The 28th International Conference on Artificial Intelligence and Statistics., 2025
@article{chen2024conditional,title={Conditional diffusions for amortized neural posterior estimation},author={Chen, Tianyu and Bansal, Vansh and Scott, James G.},journal={The 28th International Conference on Artificial Intelligence and Statistics.},year={2025},tldr={Diffusion is a good tool to do posterior sampling.},}
2024
Preprint
Enhancing and Accelerating Diffusion-Based Inverse Problem Solving through Measurements Optimization
Tianyu Chen, Zhendong Wang, and Mingyuan. Zhou
Submmitted., 2024
NeurIPS 2024
Diffusion Policies creating a Trust Region for Offline Reinforcement Learning
Tianyu Chen, Zhendong Wang, and Mingyuan Zhou
Advances in Neural Information Processing Systems 2024, 2024
@article{chen2024diffusion,title={Diffusion Policies creating a Trust Region for Offline Reinforcement Learning},author={Chen, Tianyu and Wang, Zhendong and Zhou, Mingyuan},journal={Advances in Neural Information Processing Systems 2024},year={2024},url={https://arxiv.org/abs/2405.19690},tldr={Diffusion loss can be used to distill one-step policy and encourage mode-seeking.}}
NeurIPS 2024
Identifying General Mechanism Shifts in Linear Causal Representations
Tianyu Chen, Kevin Bello, Francesco Locatello, and 2 more authors
Advances in Neural Information Processing Systems 2024, 2024
@article{chen2024identifying,title={Identifying General Mechanism Shifts in Linear Causal Representations},author={Chen, Tianyu and Bello, Kevin and Locatello, Francesco and Aragam, Bryon and Ravikumar, Pradeep},journal={Advances in Neural Information Processing Systems 2024},year={2024},}
PNAS
Model-based trajectory inference for single-cell rna sequencing using deep learning with a mixture prior
Tianyu Chen*, Jin-Hong Du*, Ming Gao, and 1 more author
Proceedings of the National Academy of Sciences, 2024
@article{du2020model,title={Model-based trajectory inference for single-cell rna sequencing using deep learning with a mixture prior},author={Chen, Tianyu and Du, Jin-Hong and Gao, Ming and Wang, Jingshu},journal={Proceedings of the National Academy of Sciences},pages={Vol. 121 | No. 37},year={2024},url={https://www.pnas.org/doi/10.1073/pnas.2316256121},tldr={A VAE with a hierarchical prior offers a comprehensive pipeline for integrating multi-omic data, correcting batch effects, inferring pseudotime, and conducting differential analysis.}}
2023
NeurIPS 2023
iSCAN: identifying causal mechanism shifts among nonlinear additive noise models
Tianyu Chen, Kevin Bello, Bryon Aragam, and 1 more author
Advances in Neural Information Processing Systems 2023, 2023
@article{chen2024iscan,title={iSCAN: identifying causal mechanism shifts among nonlinear additive noise models},author={Chen, Tianyu and Bello, Kevin and Aragam, Bryon and Ravikumar, Pradeep},journal={Advances in Neural Information Processing Systems 2023},volume={36},year={2023},url={https://arxiv.org/abs/2306.17361},tldr={Score matching help directly detect shifted nodes among different graphs.}}
@incollection{wang2022deep,title={Deep Learning Methods for Single-Cell Omics Data},author={Wang, Jingshu and Chen, Tianyu},booktitle={Handbook of Statistical Bioinformatics},pages={109--132},year={2022},publisher={Springer},tldr={An overview of machine learning methods in single cell data.},url={https://link.springer.com/chapter/10.1007/978-3-662-65902-1_6},}