Publications

2025

1. Preprint

   Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation

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

   Preprint., 2025

   PDF
2. 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

   Bib PDF Code

   @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

1. Preprint

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

   Tianyu Chen, Zhendong Wang, and Mingyuan. Zhou

   Submmitted., 2024
2. 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.}
   }

3. 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},
   }

4. 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},
   }