Publications

2025

1. Preprint

   EdiVal-Agent: An Object-Centric Framework for Automated, Scalable, Fine-Grained Evaluation of Multi-Turn Editing

   Tianyu Chen^*, Yasi Zhang^*, Zhi Zhang, and 8 more authors

   arXiv preprint arXiv:2509.13399, 2025

   Bib PDF Code Website

   @article{chen2025edival,
     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 others},
     journal = {arXiv preprint arXiv:2509.13399},
     year = {2025},
     media = {https://mp.weixin.qq.com/s/jlVDWl7wJ8SGFcGdRG7wGA},
     tldr = {An automated VLM agent for fine-grained, multi-turn image editing evaluation with media coverage.}
   }

2. NIPS2025 Spotlight

   CoLT: The conditional localization test for assessing the accuracy of neural posterior estimates

   Tianyu Chen^*, Vansh Bansal^*, and James G Scott

   arXiv preprint arXiv:2507.17030, 2025

   Bib PDF

   @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 = {arXiv preprint arXiv:2507.17030},
     year = {2025},
   }

3. Preprint

   Restoration score distillation: From corrupted diffusion pretraining to one-step high-quality generation

   Yasi Zhang^*, Tianyu Chen^*, Zhendong Wang, and 3 more authors

   arXiv preprint arXiv:2505.13377, 2025

   Bib PDF

   @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},
   }

4. Preprint

   The surprising strength of weak classifiers for validating neural posterior estimates

   Vansh Bansal^*, Tianyu Chen^*, and James G Scott

   arXiv preprint arXiv:2507.17026, 2025

   Bib PDF

   @article{bansal2025surprising,
     title = {The surprising strength of weak classifiers for validating neural posterior estimates},
     author = {Bansal, Vansh and Chen, Tianyu and Scott, James G},
     journal = {arXiv preprint arXiv:2507.17026},
     year = {2025},
   }

5. NeurIPS2025

   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

   arXiv preprint arXiv:2506.05316, 2025

   Bib PDF

   @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 = {arXiv preprint arXiv:2506.05316},
     year = {2025},
   }

6. Preprint

   A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation

   Xinran Song^*, Tianyu Chen^*, and Mingyuan Zhou

   arXiv preprint arXiv:2505.11444, 2025

   Bib PDF

   @article{song2025generative,
     title = {A Generative Framework for Causal Estimation via Importance-Weighted Diffusion Distillation},
     author = {Song, Xinran and Chen, Tianyu and Zhou, Mingyuan},
     journal = {arXiv preprint arXiv:2505.11444},
     year = {2025},
   }

7. Preprint

   Denoising score distillation: From noisy diffusion pretraining to one-step high-quality generation

   Tianyu Chen^*, Yasi Zhang^*, Zhendong Wang, and 3 more authors

   arXiv preprint arXiv:2503.07578, 2025

   Bib PDF

   @article{chen2025denoising,
     title = {Denoising score distillation: From noisy diffusion pretraining to one-step high-quality generation},
     author = {Chen, Tianyu and Zhang, Yasi and Wang, Zhendong and Wu, Ying Nian and Leong, Oscar and Zhou, Mingyuan},
     journal = {arXiv preprint arXiv:2503.07578},
     year = {2025},
     tldr = {One-step high-quality generation from diffusion models via denoising score distillation.}
   }

2024

1. Preprint

   Enhancing and Accelerating Diffusion-Based Inverse Problem Solving through Measurements Optimization

   Tianyu Chen, Zhendong Wang, and Mingyuan. Zhou

   Submmitted., 2024
2. AISTATS2025

   Conditional diffusions for neural posterior estimation

   Tianyu Chen, Vansh Bansal, and James G. Scott

   Submmitted., 2024

   PDF Code
3. NeurIPS2024

   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

   Bib PDF Code

   @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.}
   }

4. NeurIPS2024

   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

   Bib PDF Code

   @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},
   }

5. 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

   Bib PDF Code

   @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

1. NeurIPS2023

   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

   Bib PDF Code

   @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.}
   }

2022

1. Book Chapter

   Deep Learning Methods for Single-Cell Omics Data

   Jingshu Wang, and Tianyu Chen

   In Handbook of Statistical Bioinformatics, 2022

   Bib PDF

   @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},
   }