publications | Elynn Chen

For the most up-to-date list, see Google Scholar.

2026

JASA

Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection

Elynn Chen, Jiayu Li, Zheshi Zheng, and Jian Pei

Under Review, Journal of the American Statistical Association, 2026

@article{chen2026dualchannel,
  stream = {multiway},
  title = {Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection},
  author = {Chen, Elynn and Li, Jiayu and Zheng, Zheshi and Pei, Jian},
  journal = {Under Review, Journal of the American Statistical Association},
  year = {2026},
}

JASA

Data-Driven Knowledge Transfer in Batch Q-Learning

Elynn Chen, Xi Chen, and Wenbo Jing

Journal of the American Statistical Association, 121(553):276-288, 2026

DOI Bib

@article{chen2026batchq,
  stream = {heterogeneity},
  title = {Data-Driven Knowledge Transfer in Batch Q-Learning},
  author = {Chen, Elynn and Chen, Xi and Jing, Wenbo},
  journal = {Journal of the American Statistical Association, 121(553):276-288},
  year = {2026},
  doi = {10.1080/01621459.2025.2603731}
}

Mgmt. Sci.

Transfer Learning for Contextual Joint Assortment-Pricing under Cross-Market Heterogeneity

Elynn Chen, Xi Chen, and Yi Zhang

Under Review, Management Science, 2026

arXiv Bib

@article{chen2026assortment,
  stream = {heterogeneity},
  title = {Transfer Learning for Contextual Joint Assortment-Pricing under Cross-Market Heterogeneity},
  author = {Chen, Elynn and Chen, Xi and Zhang, Yi},
  journal = {Under Review, Management Science},
  year = {2026},
}

NeurIPS

One-Step Bellman Alignment Enables Provably Efficient Transfer in Online RL

Elynn Chen, Enpei Zhang, Jinhang Chai, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

arXiv Bib

@inproceedings{chen2026bellman,
  stream = {heterogeneity},
  title = {One-Step Bellman Alignment Enables Provably Efficient Transfer in Online RL},
  author = {Chen, Elynn and Zhang, Enpei and Chai, Jinhang and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026},
}

NeurIPS

Anchored Transfer for Matrix Estimation under Expanding Ambient and Representation Spaces

Elynn Chen, Jinhang Chai, Xuyuan Liu, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

arXiv Bib

@inproceedings{chen2026anchored,
  stream = {heterogeneity},
  title = {Anchored Transfer for Matrix Estimation under Expanding Ambient and Representation Spaces},
  author = {Chen, Elynn and Chai, Jinhang and Liu, Xuyuan and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026},
}

Mgmt. Sci.

Dynamic Contextual Pricing with Doubly Non-Parametric Random Utility Models

Elynn Chen, Xi Chen, Gao Lan, and Jiayu Li

Management Science, 2026

arXiv Bib

@article{chen2026pricing,
  stream = {decision},
  title = {Dynamic Contextual Pricing with Doubly Non-Parametric Random Utility Models},
  author = {Chen, Elynn and Chen, Xi and Lan, Gao and Li, Jiayu},
  journal = {Management Science},
  year = {2026},
}

ICLR

Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

Zheng Huang, Enpei Zhang, Yinghao Cai, Weikang Qiu, Carl Yang, Elynn Chen, Rex Ying, Xiang Zhang, Dawei Zhou, and Yujun Yan

In International Conference on Learning Representations (ICLR, Oral Presentation, Top 1%), 2026

arXiv Bib

@inproceedings{huang2026brain,
  stream = {decision},
  title = {Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI},
  author = {Huang, Zheng and Zhang, Enpei and Cai, Yinghao and Qiu, Weikang and Yang, Carl and Chen, Elynn and Ying, Rex and Zhang, Xiang and Zhou, Dawei and Yan, Yujun},
  booktitle = {International Conference on Learning Representations (ICLR, Oral Presentation, Top 1%)},
  year = {2026},
}

AISTATS

Quantifying Epistemic Uncertainty in Diffusion Models

Aditi Gupta, Raphael A. Meyer, Yotam Yaniv, Elynn Chen, and N. Benjamin Erichson

In International Conference on Artificial Intelligence and Statistics (AISTATS), 2026

arXiv Bib

@inproceedings{gupta2026diffusion,
  stream = {decision},
  title = {Quantifying Epistemic Uncertainty in Diffusion Models},
  author = {Gupta, Aditi and Meyer, Raphael A. and Yaniv, Yotam and Chen, Elynn and Erichson, N. Benjamin},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year = {2026},
}

NeurIPS

When Form Changes but Logic Doesn’t: Building Logic-invariant LLMs through Structures

Xuyuan Liu, Xinshuai Dong, Elynn Chen, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

Bib

@inproceedings{liu2026logic,
  stream = {decision},
  title = {When Form Changes but Logic Doesn't: Building Logic-invariant LLMs through Structures},
  author = {Liu, Xuyuan and Dong, Xinshuai and Chen, Elynn and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026}
}

NeurIPS

What Makes Language Models Intelligent? Small-World Structure in Attention Head Networks

Zheng Huang, Enpei Zhang, Weikang Qiu, Rex Ying, Elynn Chen, Yaoqing Yang, Dawei Zhou, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

Bib

@inproceedings{huang2026smallworld,
  stream = {decision},
  title = {What Makes Language Models Intelligent? Small-World Structure in Attention Head Networks},
  author = {Huang, Zheng and Zhang, Enpei and Qiu, Weikang and Ying, Rex and Chen, Elynn and Yang, Yaoqing and Zhou, Dawei and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026}
}

NeurIPS

Learning to Hand Off: Provably Convergent Workflow Learning under Interface Constraints

Jiayu Li, Enpei Zhang, Dawei Zhou, Elynn Chen, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

arXiv Bib

@inproceedings{li2026handoff,
  stream = {decision},
  title = {Learning to Hand Off: Provably Convergent Workflow Learning under Interface Constraints},
  author = {Li, Jiayu and Zhang, Enpei and Zhou, Dawei and Chen, Elynn and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026},
}

NeurIPS

Optimize Once, Execute Fast: Latency-Aware Multi-Agent Workflow Learning for Recurrent Queries

Enpei Zhang, Feiyu Qu, Zheng Huang, Dawei Zhou, Elynn Chen, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

Bib

@inproceedings{zhang2026optimize,
  stream = {decision},
  title = {Optimize Once, Execute Fast: Latency-Aware Multi-Agent Workflow Learning for Recurrent Queries},
  author = {Zhang, Enpei and Qu, Feiyu and Huang, Zheng and Zhou, Dawei and Chen, Elynn and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026}
}

2025

JASA

High-Dimensional Tensor Discriminant Analysis: Low-Rank Discriminant Structure, Representation Synergy, and Theoretical Guarantees

Elynn Chen, Yuefeng Han, and Jiayu Li

Major Revision, Journal of the American Statistical Association, 2025

arXiv Bib

@article{chen2025tda,
  stream = {multiway},
  title = {High-Dimensional Tensor Discriminant Analysis: Low-Rank Discriminant Structure, Representation Synergy, and Theoretical Guarantees},
  author = {Chen, Elynn and Han, Yuefeng and Li, Jiayu},
  journal = {Major Revision, Journal of the American Statistical Association},
  year = {2025},
}

JASA

Distributed Tensor Principal Component Analysis with Data Heterogeneity

Elynn Chen, Xi Chen, Wenbo Jing, and Yichen Zhang

Journal of the American Statistical Association, 2025

DOI Bib

@article{chen2025distributedtpca,
  stream = {multiway},
  title = {Distributed Tensor Principal Component Analysis with Data Heterogeneity},
  author = {Chen, Elynn and Chen, Xi and Jing, Wenbo and Zhang, Yichen},
  journal = {Journal of the American Statistical Association},
  year = {2025},
  doi = {10.1080/01621459.2025.2483481}
}

Ann. Stat.

Modewise Additive Factor Model for Matrix Time Series

Elynn Chen, Yuefeng Han, Jiayu Li, and Ke Xu

Major Revision, Annals of Statistics, 2025

arXiv Bib

@article{chen2025modewise,
  stream = {multiway},
  title = {Modewise Additive Factor Model for Matrix Time Series},
  author = {Chen, Elynn and Han, Yuefeng and Li, Jiayu and Xu, Ke},
  journal = {Major Revision, Annals of Statistics},
  year = {2025},
}

AoAS

Tensor Neyman-Pearson Classification: Theory, Algorithms, and Error Control

Lingchong Liu, Elynn Chen, Yuefeng Han, and Lucy Xia

Major Revision, Annals of Applied Statistics (senior advising authors ordered alphabetically), 2025

arXiv Bib

@article{liu2025tnp,
  stream = {multiway},
  title = {Tensor Neyman-Pearson Classification: Theory, Algorithms, and Error Control},
  author = {Liu, Lingchong and Chen, Elynn and Han, Yuefeng and Xia, Lucy},
  journal = {Major Revision, Annals of Applied Statistics (senior advising authors ordered alphabetically)},
  year = {2025},
}

JASA

Factor Augmented Matrix Regression

Elynn Chen, Jianqing Fan, and Xiaonan Zhu

Journal of the American Statistical Association, 2025

DOI Bib

@article{chen2025famr,
  stream = {multiway},
  title = {Factor Augmented Matrix Regression},
  author = {Chen, Elynn and Fan, Jianqing and Zhu, Xiaonan},
  journal = {Journal of the American Statistical Association},
  year = {2025},
  doi = {10.1080/01621459.2025.2595734}
}

IEEE T-IT

High-Dimensional Tensor Discriminant Analysis with Incomplete Tensors

Elynn Chen, Yuefeng Han, and Jiayu Li

Major Revision, IEEE Transactions on Information Theory, 2025

arXiv Bib

@article{chen2025incomplete,
  stream = {multiway},
  title = {High-Dimensional Tensor Discriminant Analysis with Incomplete Tensors},
  author = {Chen, Elynn and Han, Yuefeng and Li, Jiayu},
  journal = {Major Revision, IEEE Transactions on Information Theory},
  year = {2025},
}

JASA

Modeling Multivariate Spatial-Temporal Data with Latent Low-Dimensional Dynamics

Elynn Chen, Xin Yun, Qiwei Yao, and Rong Chen

Major Revision, Journal of the American Statistical Association, 2025

arXiv Bib

@article{chen2025spatiotemporal,
  stream = {multiway},
  title = {Modeling Multivariate Spatial-Temporal Data with Latent Low-Dimensional Dynamics},
  author = {Chen, Elynn and Yun, Xin and Yao, Qiwei and Chen, Rong},
  journal = {Major Revision, Journal of the American Statistical Association},
  year = {2025},
}

JRSS-B

Time-Varying Matrix Factor Models

Bin Chen, Elynn Chen, Stevenson Bolivar Atuesta, and Rong Chen

Under Review, Journal of the Royal Statistical Society: Series B, 2025

arXiv Bib

@article{chen2025tvmfm,
  stream = {multiway},
  title = {Time-Varying Matrix Factor Models},
  author = {Chen, Bin and Chen, Elynn and Bolivar Atuesta, Stevenson and Chen, Rong},
  journal = {Under Review, Journal of the Royal Statistical Society: Series B},
  year = {2025},
}

AISTATS

Conditional Prediction ROC Bands for Tensor Graph Classification

Yujia Wu, Bo Yang, Elynn Chen, Yuzhou Chen, and Zheshi Zheng

In International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 258:2458-2466, 2025

Bib

@inproceedings{wu2025rocbands,
  stream = {multiway},
  title = {Conditional Prediction ROC Bands for Tensor Graph Classification},
  author = {Wu, Yujia and Yang, Bo and Chen, Elynn and Chen, Yuzhou and Zheng, Zheshi},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 258:2458-2466},
  year = {2025}
}

IJCAI-W

TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting

Linghang Kong, Elynn Chen, Yuzhou Chen, and Yuefeng Han

In IJCAI 2025 Workshop on AI for Time Series, 2025

Bib

@inproceedings{kong2025teaformers,
  stream = {multiway},
  title = {TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting},
  author = {Kong, Linghang and Chen, Elynn and Chen, Yuzhou and Han, Yuefeng},
  booktitle = {IJCAI 2025 Workshop on AI for Time Series},
  year = {2025}
}

PAKDD

Tensor-Fused Multi-View Graph Contrastive Learning

Yujia Wu, Junyi Mo, Elynn Chen, and Yuzhou Chen

In Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2025

DOI Bib

@inproceedings{wu2025tensorfused,
  stream = {multiway},
  title = {Tensor-Fused Multi-View Graph Contrastive Learning},
  author = {Wu, Yujia and Mo, Junyi and Chen, Elynn and Chen, Yuzhou},
  booktitle = {Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)},
  year = {2025},
  doi = {10.1007/978-981-96-8298-0_2}
}

CPAL

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation

Tao Wen, Elynn Chen, Yuzhou Chen, and Qi Lei

In Conference on Parsimony and Learning (CPAL), PMLR 280:599-614, 2025

Bib

@inproceedings{wen2025bridging,
  stream = {multiway},
  title = {Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation},
  author = {Wen, Tao and Chen, Elynn and Chen, Yuzhou and Lei, Qi},
  booktitle = {Conference on Parsimony and Learning (CPAL), PMLR 280:599-614},
  year = {2025}
}

Chapter

Advancing Information Integration through Empirical Likelihood: Selective Reviews and a New Idea

Chixiang Chen, Jia Liang, Elynn Chen, and Ming Wang

In Springer Book on Big Data Analysis, Biostatistics and Bioinformatics, 2025

arXiv Bib

@incollection{chen2025empirical,
  stream = {multiway},
  title = {Advancing Information Integration through Empirical Likelihood: Selective Reviews and a New Idea},
  author = {Chen, Chixiang and Liang, Jia and Chen, Elynn and Wang, Ming},
  booktitle = {Springer Book on Big Data Analysis, Biostatistics and Bioinformatics},
  year = {2025},
}

Ann. Stat.

Deep Transfer Q-Learning for Offline Non-Stationary Reinforcement Learning

Jinhang Chai, Elynn Chen, and Jianqing Fan

Revised and Resubmitted, Annals of Statistics, 2025

arXiv Bib

@article{chai2025deeptransfer,
  stream = {heterogeneity},
  title = {Deep Transfer Q-Learning for Offline Non-Stationary Reinforcement Learning},
  author = {Chai, Jinhang and Chen, Elynn and Fan, Jianqing},
  journal = {Revised and Resubmitted, Annals of Statistics},
  year = {2025},
}

EJS

Transfer Q-Learning for Finite-Horizon Markov Decision Processes

Elynn Chen, Sai Li, and Michael I. Jordan

Electronic Journal of Statistics, 19(2):5289-5312, 2025

DOI Bib

@article{chen2025transferq,
  stream = {heterogeneity},
  title = {Transfer Q-Learning for Finite-Horizon Markov Decision Processes},
  author = {Chen, Elynn and Li, Sai and Jordan, Michael I.},
  journal = {Electronic Journal of Statistics, 19(2):5289-5312},
  year = {2025},
  doi = {10.1214/25-EJS2459}
}

Stat. Med.

Exploring Causal Effects of Hormone- and Radio-Treatments in an Observational Study of Breast Cancer Using Copula-Based Semi-Competing Risks Models

Tonghui Yu, Mengjiao Peng, Yifan Cui, Elynn Chen, and Chixiang Chen

Statistics in Medicine, 2025

DOI Bib

@article{yu2025copula,
  stream = {heterogeneity},
  title = {Exploring Causal Effects of Hormone- and Radio-Treatments in an Observational Study of Breast Cancer Using Copula-Based Semi-Competing Risks Models},
  author = {Yu, Tonghui and Peng, Mengjiao and Cui, Yifan and Chen, Elynn and Chen, Chixiang},
  journal = {Statistics in Medicine},
  year = {2025},
  doi = {10.1002/sim.70131}
}

JMLR

Stochastic Linear Bandits in a Latent Heterogeneous Environment

Elynn Chen, Xi Chen, Wenbo Jing, and Xiao Liu

Under Review, Journal of Machine Learning Research, 2025

arXiv Bib

@article{chen2025bandits,
  stream = {heterogeneity},
  title = {Stochastic Linear Bandits in a Latent Heterogeneous Environment},
  author = {Chen, Elynn and Chen, Xi and Jing, Wenbo and Liu, Xiao},
  journal = {Under Review, Journal of Machine Learning Research},
  year = {2025},
}

NeurIPS

Transfer Faster, Price Smarter: Minimax Dynamic Pricing under Cross-Market Preference Shift

Yi Zhang, Elynn Chen, and Yujun Yan

In Advances in Neural Information Processing Systems (NeurIPS, Spotlight, Top 2%), 2025

arXiv Bib

@inproceedings{zhang2025transferpricing,
  stream = {heterogeneity},
  title = {Transfer Faster, Price Smarter: Minimax Dynamic Pricing under Cross-Market Preference Shift},
  author = {Zhang, Yi and Chen, Elynn and Yan, Yujun},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS, Spotlight, Top 2%)},
  year = {2025},
}

ICML

Transfer Q-Learning with Composite Markov Decision Processes

Jinhang Chai, Elynn Chen, and Lin Yang

In International Conference on Machine Learning (ICML), PMLR 267:7089-7106, 2025

Bib

@inproceedings{chai2025composite,
  stream = {heterogeneity},
  title = {Transfer Q-Learning with Composite Markov Decision Processes},
  author = {Chai, Jinhang and Chen, Elynn and Yang, Lin},
  booktitle = {International Conference on Machine Learning (ICML), PMLR 267:7089-7106},
  year = {2025}
}

ICAIF

Time-Varying Factor-Augmented Models for Volatility Forecasting

Duo Zhang, Jiayu Li, Junyi Mo, and Elynn Chen

In ACM International Conference on AI in Finance (ICAIF), 2025

DOI Bib

@inproceedings{zhang2025volatility,
  stream = {decision},
  title = {Time-Varying Factor-Augmented Models for Volatility Forecasting},
  author = {Zhang, Duo and Li, Jiayu and Mo, Junyi and Chen, Elynn},
  booktitle = {ACM International Conference on AI in Finance (ICAIF)},
  year = {2025},
  doi = {10.1145/3768292.3770407}
}

ICAIF

ACT-Tensor: Tensor Completion Framework for Financial Dataset Imputation

Junyi Mo, Jiayu Li, Duo Zhang, and Elynn Chen

In ACM International Conference on AI in Finance (ICAIF), 2025

DOI Bib

@inproceedings{mo2025acttensor,
  stream = {decision},
  title = {ACT-Tensor: Tensor Completion Framework for Financial Dataset Imputation},
  author = {Mo, Junyi and Li, Jiayu and Zhang, Duo and Chen, Elynn},
  booktitle = {ACM International Conference on AI in Finance (ICAIF)},
  year = {2025},
  doi = {10.1145/3768292.3770408}
}

ACM EC

Maximal Extractable Value in Batch Auctions

Mengqian Zhang, Yuhao Li, Xinyuan Sun, Elynn Chen, and Xi Chen

In ACM Conference on Economics and Computation (EC), 2025

DOI Bib

@inproceedings{zhang2025mev,
  stream = {decision},
  title = {Maximal Extractable Value in Batch Auctions},
  author = {Zhang, Mengqian and Li, Yuhao and Sun, Xinyuan and Chen, Elynn and Chen, Xi},
  booktitle = {ACM Conference on Economics and Computation (EC)},
  year = {2025},
  doi = {10.1145/3736252.3742581}
}

2024

JRSS-B

Semiparametric Tensor Factor Analysis by Iteratively Projected SVD

Elynn Chen, Dong Xia, Chencheng Cai, and Jianqing Fan

Journal of the Royal Statistical Society: Series B, 2024

DOI Bib

@article{chen2024stefa,
  stream = {multiway},
  title = {Semiparametric Tensor Factor Analysis by Iteratively Projected SVD},
  author = {Chen, Elynn and Xia, Dong and Cai, Chencheng and Fan, Jianqing},
  journal = {Journal of the Royal Statistical Society: Series B},
  year = {2024},
  doi = {10.1093/jrsssb/qkae001}
}

AISTATS

Tensor-view Topological Graph Neural Network

Tao Wen, Elynn Chen, and Yuzhou Chen

In International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 238:4330-4338, 2024

arXiv Bib Code

@inproceedings{wen2024ttgnn,
  stream = {multiway},
  title = {Tensor-view Topological Graph Neural Network},
  author = {Wen, Tao and Chen, Elynn and Chen, Yuzhou},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 238:4330-4338},
  year = {2024},
}

JASA

Reinforcement Learning in Latent Heterogeneous Environments

Elynn Chen, Rui Song, and Michael I. Jordan

Journal of the American Statistical Association, 119(548):3113-3126, 2024

DOI Bib

@article{chen2024heterorl,
  stream = {heterogeneity},
  title = {Reinforcement Learning in Latent Heterogeneous Environments},
  author = {Chen, Elynn and Song, Rui and Jordan, Michael I.},
  journal = {Journal of the American Statistical Association, 119(548):3113-3126},
  year = {2024},
  doi = {10.1080/01621459.2024.2308317}
}

2023

JASA

Statistical Inference for High-Dimensional Matrix-Variate Factor Models

Elynn Chen and Jianqing Fan

Journal of the American Statistical Association, 2023

DOI Bib

@article{chen2023inference,
  stream = {multiway},
  title = {Statistical Inference for High-Dimensional Matrix-Variate Factor Models},
  author = {Chen, Elynn and Fan, Jianqing},
  journal = {Journal of the American Statistical Association},
  year = {2023},
  doi = {10.1080/01621459.2021.1970569}
}

J. Econom.

Community Network Auto-Regression for High-Dimensional Time Series

Elynn Chen, Jianqing Fan, and Xuening Zhu

Journal of Econometrics, 2023

DOI Bib

@article{chen2023cnar,
  stream = {multiway},
  title = {Community Network Auto-Regression for High-Dimensional Time Series},
  author = {Chen, Elynn and Fan, Jianqing and Zhu, Xuening},
  journal = {Journal of Econometrics},
  year = {2023},
  doi = {10.1016/j.jeconom.2022.10.005}
}

DeFi

MEV Makes Everyone Happy under Greedy Sequencing Rule

Yuhao Li, Mengqian Zhang, Jichen Li, Elynn Chen, Xi Chen, and Xiaotie Deng

In Proceedings of the 2023 Workshop on Decentralized Finance and Security, pp. 9-15, 2023

DOI Bib

@inproceedings{li2023mev,
  stream = {decision},
  title = {MEV Makes Everyone Happy under Greedy Sequencing Rule},
  author = {Li, Yuhao and Zhang, Mengqian and Li, Jichen and Chen, Elynn and Chen, Xi and Deng, Xiaotie},
  booktitle = {Proceedings of the 2023 Workshop on Decentralized Finance and Security, pp. 9-15},
  year = {2023},
  doi = {10.1145/3605768.3623543}
}

2022

Scand. J. Stat.

Identification and Estimation of Threshold Matrix-Variate Factor Models

Xialu Liu and Elynn Chen

Scandinavian Journal of Statistics, 2022

DOI Bib

@article{liu2022threshold,
  stream = {multiway},
  title = {Identification and Estimation of Threshold Matrix-Variate Factor Models},
  author = {Liu, Xialu and Chen, Elynn},
  journal = {Scandinavian Journal of Statistics},
  year = {2022},
  doi = {10.1111/sjos.12576}
}

J. Data Sci.

Modeling Dynamic Transport Network with Low-Rank Matrix-variate Time Series: an Application to International Trade Flow

Elynn Chen and Rong Chen

Journal of Data Science, 2022

DOI Bib

@article{chen2022transport,
  stream = {decision},
  title = {Modeling Dynamic Transport Network with Low-Rank Matrix-variate Time Series: an Application to International Trade Flow},
  author = {Chen, Elynn and Chen, Rong},
  journal = {Journal of Data Science},
  year = {2022},
  doi = {10.6339/22-JDS1065}
}

2021

AISTATS

On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification

Tianyi Lin, Zeyu Zheng, Elynn Chen, Marco Cuturi, and Michael I. Jordan

In International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 130:262-270, 2021

arXiv Bib

@inproceedings{lin2021prw,
  stream = {heterogeneity},
  title = {On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification},
  author = {Lin, Tianyi and Zheng, Zeyu and Chen, Elynn and Cuturi, Marco and Jordan, Michael I.},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 130:262-270},
  year = {2021},
}

2019

JASA

Constrained Factor Models for High-Dimensional Matrix-Variate Time Series

Elynn Chen, Ruey S. Tsay, and Rong Chen

Journal of the American Statistical Association, 2019

DOI Bib

@article{chen2019constrained,
  stream = {multiway},
  title = {Constrained Factor Models for High-Dimensional Matrix-Variate Time Series},
  author = {Chen, Elynn and Tsay, Ruey S. and Chen, Rong},
  journal = {Journal of the American Statistical Association},
  year = {2019},
  doi = {10.1080/01621459.2019.1584899}
}

Structured multi-way statistical learning

Matrix, tensor, network, and spatial-temporal data; tensor-structured neural networks.

2026

JASA

Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection

Elynn Chen, Jiayu Li, Zheshi Zheng, and Jian Pei

Under Review, Journal of the American Statistical Association, 2026

arXiv Bib

@article{chen2026dualchannel,
  stream = {multiway},
  title = {Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection},
  author = {Chen, Elynn and Li, Jiayu and Zheng, Zheshi and Pei, Jian},
  journal = {Under Review, Journal of the American Statistical Association},
  year = {2026},
}

2025

JASA

High-Dimensional Tensor Discriminant Analysis: Low-Rank Discriminant Structure, Representation Synergy, and Theoretical Guarantees

Elynn Chen, Yuefeng Han, and Jiayu Li

Major Revision, Journal of the American Statistical Association, 2025

arXiv Bib

@article{chen2025tda,
  stream = {multiway},
  title = {High-Dimensional Tensor Discriminant Analysis: Low-Rank Discriminant Structure, Representation Synergy, and Theoretical Guarantees},
  author = {Chen, Elynn and Han, Yuefeng and Li, Jiayu},
  journal = {Major Revision, Journal of the American Statistical Association},
  year = {2025},
}

JASA

Distributed Tensor Principal Component Analysis with Data Heterogeneity

Elynn Chen, Xi Chen, Wenbo Jing, and Yichen Zhang

Journal of the American Statistical Association, 2025

DOI Bib

@article{chen2025distributedtpca,
  stream = {multiway},
  title = {Distributed Tensor Principal Component Analysis with Data Heterogeneity},
  author = {Chen, Elynn and Chen, Xi and Jing, Wenbo and Zhang, Yichen},
  journal = {Journal of the American Statistical Association},
  year = {2025},
  doi = {10.1080/01621459.2025.2483481}
}

Ann. Stat.

Modewise Additive Factor Model for Matrix Time Series

Elynn Chen, Yuefeng Han, Jiayu Li, and Ke Xu

Major Revision, Annals of Statistics, 2025

arXiv Bib

@article{chen2025modewise,
  stream = {multiway},
  title = {Modewise Additive Factor Model for Matrix Time Series},
  author = {Chen, Elynn and Han, Yuefeng and Li, Jiayu and Xu, Ke},
  journal = {Major Revision, Annals of Statistics},
  year = {2025},
}

AoAS

Tensor Neyman-Pearson Classification: Theory, Algorithms, and Error Control

Lingchong Liu, Elynn Chen, Yuefeng Han, and Lucy Xia

Major Revision, Annals of Applied Statistics (senior advising authors ordered alphabetically), 2025

arXiv Bib

@article{liu2025tnp,
  stream = {multiway},
  title = {Tensor Neyman-Pearson Classification: Theory, Algorithms, and Error Control},
  author = {Liu, Lingchong and Chen, Elynn and Han, Yuefeng and Xia, Lucy},
  journal = {Major Revision, Annals of Applied Statistics (senior advising authors ordered alphabetically)},
  year = {2025},
}

JASA

Factor Augmented Matrix Regression

Elynn Chen, Jianqing Fan, and Xiaonan Zhu

Journal of the American Statistical Association, 2025

DOI Bib

@article{chen2025famr,
  stream = {multiway},
  title = {Factor Augmented Matrix Regression},
  author = {Chen, Elynn and Fan, Jianqing and Zhu, Xiaonan},
  journal = {Journal of the American Statistical Association},
  year = {2025},
  doi = {10.1080/01621459.2025.2595734}
}

IEEE T-IT

High-Dimensional Tensor Discriminant Analysis with Incomplete Tensors

Elynn Chen, Yuefeng Han, and Jiayu Li

Major Revision, IEEE Transactions on Information Theory, 2025

arXiv Bib

@article{chen2025incomplete,
  stream = {multiway},
  title = {High-Dimensional Tensor Discriminant Analysis with Incomplete Tensors},
  author = {Chen, Elynn and Han, Yuefeng and Li, Jiayu},
  journal = {Major Revision, IEEE Transactions on Information Theory},
  year = {2025},
}

JASA

Modeling Multivariate Spatial-Temporal Data with Latent Low-Dimensional Dynamics

Elynn Chen, Xin Yun, Qiwei Yao, and Rong Chen

Major Revision, Journal of the American Statistical Association, 2025

arXiv Bib

@article{chen2025spatiotemporal,
  stream = {multiway},
  title = {Modeling Multivariate Spatial-Temporal Data with Latent Low-Dimensional Dynamics},
  author = {Chen, Elynn and Yun, Xin and Yao, Qiwei and Chen, Rong},
  journal = {Major Revision, Journal of the American Statistical Association},
  year = {2025},
}

JRSS-B

Time-Varying Matrix Factor Models

Bin Chen, Elynn Chen, Stevenson Bolivar Atuesta, and Rong Chen

Under Review, Journal of the Royal Statistical Society: Series B, 2025

arXiv Bib

@article{chen2025tvmfm,
  stream = {multiway},
  title = {Time-Varying Matrix Factor Models},
  author = {Chen, Bin and Chen, Elynn and Bolivar Atuesta, Stevenson and Chen, Rong},
  journal = {Under Review, Journal of the Royal Statistical Society: Series B},
  year = {2025},
}

AISTATS

Conditional Prediction ROC Bands for Tensor Graph Classification

Yujia Wu, Bo Yang, Elynn Chen, Yuzhou Chen, and Zheshi Zheng

In International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 258:2458-2466, 2025

Bib

@inproceedings{wu2025rocbands,
  stream = {multiway},
  title = {Conditional Prediction ROC Bands for Tensor Graph Classification},
  author = {Wu, Yujia and Yang, Bo and Chen, Elynn and Chen, Yuzhou and Zheng, Zheshi},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 258:2458-2466},
  year = {2025}
}

IJCAI-W

TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting

Linghang Kong, Elynn Chen, Yuzhou Chen, and Yuefeng Han

In IJCAI 2025 Workshop on AI for Time Series, 2025

Bib

@inproceedings{kong2025teaformers,
  stream = {multiway},
  title = {TEAFormers: TEnsor-Augmented Transformers for Multi-Dimensional Time Series Forecasting},
  author = {Kong, Linghang and Chen, Elynn and Chen, Yuzhou and Han, Yuefeng},
  booktitle = {IJCAI 2025 Workshop on AI for Time Series},
  year = {2025}
}

PAKDD

Tensor-Fused Multi-View Graph Contrastive Learning

Yujia Wu, Junyi Mo, Elynn Chen, and Yuzhou Chen

In Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2025

DOI Bib

@inproceedings{wu2025tensorfused,
  stream = {multiway},
  title = {Tensor-Fused Multi-View Graph Contrastive Learning},
  author = {Wu, Yujia and Mo, Junyi and Chen, Elynn and Chen, Yuzhou},
  booktitle = {Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)},
  year = {2025},
  doi = {10.1007/978-981-96-8298-0_2}
}

CPAL

Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation

Tao Wen, Elynn Chen, Yuzhou Chen, and Qi Lei

In Conference on Parsimony and Learning (CPAL), PMLR 280:599-614, 2025

Bib

@inproceedings{wen2025bridging,
  stream = {multiway},
  title = {Bridging Domain Adaptation and Graph Neural Networks: A Tensor-Based Framework for Effective Label Propagation},
  author = {Wen, Tao and Chen, Elynn and Chen, Yuzhou and Lei, Qi},
  booktitle = {Conference on Parsimony and Learning (CPAL), PMLR 280:599-614},
  year = {2025}
}

Chapter

Advancing Information Integration through Empirical Likelihood: Selective Reviews and a New Idea

Chixiang Chen, Jia Liang, Elynn Chen, and Ming Wang

In Springer Book on Big Data Analysis, Biostatistics and Bioinformatics, 2025

arXiv Bib

@incollection{chen2025empirical,
  stream = {multiway},
  title = {Advancing Information Integration through Empirical Likelihood: Selective Reviews and a New Idea},
  author = {Chen, Chixiang and Liang, Jia and Chen, Elynn and Wang, Ming},
  booktitle = {Springer Book on Big Data Analysis, Biostatistics and Bioinformatics},
  year = {2025},
}

2024

JRSS-B

Semiparametric Tensor Factor Analysis by Iteratively Projected SVD

Elynn Chen, Dong Xia, Chencheng Cai, and Jianqing Fan

Journal of the Royal Statistical Society: Series B, 2024

DOI Bib

@article{chen2024stefa,
  stream = {multiway},
  title = {Semiparametric Tensor Factor Analysis by Iteratively Projected SVD},
  author = {Chen, Elynn and Xia, Dong and Cai, Chencheng and Fan, Jianqing},
  journal = {Journal of the Royal Statistical Society: Series B},
  year = {2024},
  doi = {10.1093/jrsssb/qkae001}
}

AISTATS

Tensor-view Topological Graph Neural Network

Tao Wen, Elynn Chen, and Yuzhou Chen

In International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 238:4330-4338, 2024

arXiv Bib Code

@inproceedings{wen2024ttgnn,
  stream = {multiway},
  title = {Tensor-view Topological Graph Neural Network},
  author = {Wen, Tao and Chen, Elynn and Chen, Yuzhou},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 238:4330-4338},
  year = {2024},
}

2023

JASA

Statistical Inference for High-Dimensional Matrix-Variate Factor Models

Elynn Chen and Jianqing Fan

Journal of the American Statistical Association, 2023

DOI Bib

@article{chen2023inference,
  stream = {multiway},
  title = {Statistical Inference for High-Dimensional Matrix-Variate Factor Models},
  author = {Chen, Elynn and Fan, Jianqing},
  journal = {Journal of the American Statistical Association},
  year = {2023},
  doi = {10.1080/01621459.2021.1970569}
}

J. Econom.

Community Network Auto-Regression for High-Dimensional Time Series

Elynn Chen, Jianqing Fan, and Xuening Zhu

Journal of Econometrics, 2023

DOI Bib

@article{chen2023cnar,
  stream = {multiway},
  title = {Community Network Auto-Regression for High-Dimensional Time Series},
  author = {Chen, Elynn and Fan, Jianqing and Zhu, Xuening},
  journal = {Journal of Econometrics},
  year = {2023},
  doi = {10.1016/j.jeconom.2022.10.005}
}

2022

Scand. J. Stat.

Identification and Estimation of Threshold Matrix-Variate Factor Models

Xialu Liu and Elynn Chen

Scandinavian Journal of Statistics, 2022

DOI Bib

@article{liu2022threshold,
  stream = {multiway},
  title = {Identification and Estimation of Threshold Matrix-Variate Factor Models},
  author = {Liu, Xialu and Chen, Elynn},
  journal = {Scandinavian Journal of Statistics},
  year = {2022},
  doi = {10.1111/sjos.12576}
}

2019

JASA

Constrained Factor Models for High-Dimensional Matrix-Variate Time Series

Elynn Chen, Ruey S. Tsay, and Rong Chen

Journal of the American Statistical Association, 2019

DOI Bib

@article{chen2019constrained,
  stream = {multiway},
  title = {Constrained Factor Models for High-Dimensional Matrix-Variate Time Series},
  author = {Chen, Elynn and Tsay, Ruey S. and Chen, Rong},
  journal = {Journal of the American Statistical Association},
  year = {2019},
  doi = {10.1080/01621459.2019.1584899}
}

Learning and decision-making under heterogeneity

Transfer reinforcement learning, latent structure discovery, bandits, and dynamic pricing.

2026

JASA

Data-Driven Knowledge Transfer in Batch Q-Learning

Elynn Chen, Xi Chen, and Wenbo Jing

Journal of the American Statistical Association, 121(553):276-288, 2026

DOI Bib

@article{chen2026batchq,
  stream = {heterogeneity},
  title = {Data-Driven Knowledge Transfer in Batch Q-Learning},
  author = {Chen, Elynn and Chen, Xi and Jing, Wenbo},
  journal = {Journal of the American Statistical Association, 121(553):276-288},
  year = {2026},
  doi = {10.1080/01621459.2025.2603731}
}

Mgmt. Sci.

Transfer Learning for Contextual Joint Assortment-Pricing under Cross-Market Heterogeneity

Elynn Chen, Xi Chen, and Yi Zhang

Under Review, Management Science, 2026

arXiv Bib

@article{chen2026assortment,
  stream = {heterogeneity},
  title = {Transfer Learning for Contextual Joint Assortment-Pricing under Cross-Market Heterogeneity},
  author = {Chen, Elynn and Chen, Xi and Zhang, Yi},
  journal = {Under Review, Management Science},
  year = {2026},
}

NeurIPS

One-Step Bellman Alignment Enables Provably Efficient Transfer in Online RL

Elynn Chen, Enpei Zhang, Jinhang Chai, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

arXiv Bib

@inproceedings{chen2026bellman,
  stream = {heterogeneity},
  title = {One-Step Bellman Alignment Enables Provably Efficient Transfer in Online RL},
  author = {Chen, Elynn and Zhang, Enpei and Chai, Jinhang and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026},
}

NeurIPS

Anchored Transfer for Matrix Estimation under Expanding Ambient and Representation Spaces

Elynn Chen, Jinhang Chai, Xuyuan Liu, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

arXiv Bib

@inproceedings{chen2026anchored,
  stream = {heterogeneity},
  title = {Anchored Transfer for Matrix Estimation under Expanding Ambient and Representation Spaces},
  author = {Chen, Elynn and Chai, Jinhang and Liu, Xuyuan and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026},
}

2025

Ann. Stat.

Deep Transfer Q-Learning for Offline Non-Stationary Reinforcement Learning

Jinhang Chai, Elynn Chen, and Jianqing Fan

Revised and Resubmitted, Annals of Statistics, 2025

arXiv Bib

@article{chai2025deeptransfer,
  stream = {heterogeneity},
  title = {Deep Transfer Q-Learning for Offline Non-Stationary Reinforcement Learning},
  author = {Chai, Jinhang and Chen, Elynn and Fan, Jianqing},
  journal = {Revised and Resubmitted, Annals of Statistics},
  year = {2025},
}

EJS

Transfer Q-Learning for Finite-Horizon Markov Decision Processes

Elynn Chen, Sai Li, and Michael I. Jordan

Electronic Journal of Statistics, 19(2):5289-5312, 2025

DOI Bib

@article{chen2025transferq,
  stream = {heterogeneity},
  title = {Transfer Q-Learning for Finite-Horizon Markov Decision Processes},
  author = {Chen, Elynn and Li, Sai and Jordan, Michael I.},
  journal = {Electronic Journal of Statistics, 19(2):5289-5312},
  year = {2025},
  doi = {10.1214/25-EJS2459}
}

Stat. Med.

Exploring Causal Effects of Hormone- and Radio-Treatments in an Observational Study of Breast Cancer Using Copula-Based Semi-Competing Risks Models

Tonghui Yu, Mengjiao Peng, Yifan Cui, Elynn Chen, and Chixiang Chen

Statistics in Medicine, 2025

DOI Bib

@article{yu2025copula,
  stream = {heterogeneity},
  title = {Exploring Causal Effects of Hormone- and Radio-Treatments in an Observational Study of Breast Cancer Using Copula-Based Semi-Competing Risks Models},
  author = {Yu, Tonghui and Peng, Mengjiao and Cui, Yifan and Chen, Elynn and Chen, Chixiang},
  journal = {Statistics in Medicine},
  year = {2025},
  doi = {10.1002/sim.70131}
}

JMLR

Stochastic Linear Bandits in a Latent Heterogeneous Environment

Elynn Chen, Xi Chen, Wenbo Jing, and Xiao Liu

Under Review, Journal of Machine Learning Research, 2025

arXiv Bib

@article{chen2025bandits,
  stream = {heterogeneity},
  title = {Stochastic Linear Bandits in a Latent Heterogeneous Environment},
  author = {Chen, Elynn and Chen, Xi and Jing, Wenbo and Liu, Xiao},
  journal = {Under Review, Journal of Machine Learning Research},
  year = {2025},
}

NeurIPS

Transfer Faster, Price Smarter: Minimax Dynamic Pricing under Cross-Market Preference Shift

Yi Zhang, Elynn Chen, and Yujun Yan

In Advances in Neural Information Processing Systems (NeurIPS, Spotlight, Top 2%), 2025

arXiv Bib

@inproceedings{zhang2025transferpricing,
  stream = {heterogeneity},
  title = {Transfer Faster, Price Smarter: Minimax Dynamic Pricing under Cross-Market Preference Shift},
  author = {Zhang, Yi and Chen, Elynn and Yan, Yujun},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS, Spotlight, Top 2%)},
  year = {2025},
}

ICML

Transfer Q-Learning with Composite Markov Decision Processes

Jinhang Chai, Elynn Chen, and Lin Yang

In International Conference on Machine Learning (ICML), PMLR 267:7089-7106, 2025

Bib

@inproceedings{chai2025composite,
  stream = {heterogeneity},
  title = {Transfer Q-Learning with Composite Markov Decision Processes},
  author = {Chai, Jinhang and Chen, Elynn and Yang, Lin},
  booktitle = {International Conference on Machine Learning (ICML), PMLR 267:7089-7106},
  year = {2025}
}

2024

JASA

Reinforcement Learning in Latent Heterogeneous Environments

Elynn Chen, Rui Song, and Michael I. Jordan

Journal of the American Statistical Association, 119(548):3113-3126, 2024

DOI Bib

@article{chen2024heterorl,
  stream = {heterogeneity},
  title = {Reinforcement Learning in Latent Heterogeneous Environments},
  author = {Chen, Elynn and Song, Rui and Jordan, Michael I.},
  journal = {Journal of the American Statistical Association, 119(548):3113-3126},
  year = {2024},
  doi = {10.1080/01621459.2024.2308317}
}

2021

AISTATS

On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification

Tianyi Lin, Zeyu Zheng, Elynn Chen, Marco Cuturi, and Michael I. Jordan

In International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 130:262-270, 2021

arXiv Bib

@inproceedings{lin2021prw,
  stream = {heterogeneity},
  title = {On Projection Robust Optimal Transport: Sample Complexity and Model Misspecification},
  author = {Lin, Tianyi and Zheng, Zeyu and Chen, Elynn and Cuturi, Marco and Jordan, Michael I.},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 130:262-270},
  year = {2021},
}

Statistical decision analytics for business and AI systems

Pricing, finance, market design, generative AI, and agentic AI.

2026

Mgmt. Sci.

Dynamic Contextual Pricing with Doubly Non-Parametric Random Utility Models

Elynn Chen, Xi Chen, Gao Lan, and Jiayu Li

Management Science, 2026

arXiv Bib

@article{chen2026pricing,
  stream = {decision},
  title = {Dynamic Contextual Pricing with Doubly Non-Parametric Random Utility Models},
  author = {Chen, Elynn and Chen, Xi and Lan, Gao and Li, Jiayu},
  journal = {Management Science},
  year = {2026},
}

ICLR

Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

Zheng Huang, Enpei Zhang, Yinghao Cai, Weikang Qiu, Carl Yang, Elynn Chen, Rex Ying, Xiang Zhang, Dawei Zhou, and Yujun Yan

In International Conference on Learning Representations (ICLR, Oral Presentation, Top 1%), 2026

arXiv Bib

@inproceedings{huang2026brain,
  stream = {decision},
  title = {Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI},
  author = {Huang, Zheng and Zhang, Enpei and Cai, Yinghao and Qiu, Weikang and Yang, Carl and Chen, Elynn and Ying, Rex and Zhang, Xiang and Zhou, Dawei and Yan, Yujun},
  booktitle = {International Conference on Learning Representations (ICLR, Oral Presentation, Top 1%)},
  year = {2026},
}

AISTATS

Quantifying Epistemic Uncertainty in Diffusion Models

Aditi Gupta, Raphael A. Meyer, Yotam Yaniv, Elynn Chen, and N. Benjamin Erichson

In International Conference on Artificial Intelligence and Statistics (AISTATS), 2026

arXiv Bib

@inproceedings{gupta2026diffusion,
  stream = {decision},
  title = {Quantifying Epistemic Uncertainty in Diffusion Models},
  author = {Gupta, Aditi and Meyer, Raphael A. and Yaniv, Yotam and Chen, Elynn and Erichson, N. Benjamin},
  booktitle = {International Conference on Artificial Intelligence and Statistics (AISTATS)},
  year = {2026},
}

NeurIPS

When Form Changes but Logic Doesn’t: Building Logic-invariant LLMs through Structures

Xuyuan Liu, Xinshuai Dong, Elynn Chen, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

Bib

@inproceedings{liu2026logic,
  stream = {decision},
  title = {When Form Changes but Logic Doesn't: Building Logic-invariant LLMs through Structures},
  author = {Liu, Xuyuan and Dong, Xinshuai and Chen, Elynn and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026}
}

NeurIPS

What Makes Language Models Intelligent? Small-World Structure in Attention Head Networks

Zheng Huang, Enpei Zhang, Weikang Qiu, Rex Ying, Elynn Chen, Yaoqing Yang, Dawei Zhou, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

Bib

@inproceedings{huang2026smallworld,
  stream = {decision},
  title = {What Makes Language Models Intelligent? Small-World Structure in Attention Head Networks},
  author = {Huang, Zheng and Zhang, Enpei and Qiu, Weikang and Ying, Rex and Chen, Elynn and Yang, Yaoqing and Zhou, Dawei and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026}
}

NeurIPS

Learning to Hand Off: Provably Convergent Workflow Learning under Interface Constraints

Jiayu Li, Enpei Zhang, Dawei Zhou, Elynn Chen, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

arXiv Bib

@inproceedings{li2026handoff,
  stream = {decision},
  title = {Learning to Hand Off: Provably Convergent Workflow Learning under Interface Constraints},
  author = {Li, Jiayu and Zhang, Enpei and Zhou, Dawei and Chen, Elynn and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026},
}

NeurIPS

Optimize Once, Execute Fast: Latency-Aware Multi-Agent Workflow Learning for Recurrent Queries

Enpei Zhang, Feiyu Qu, Zheng Huang, Dawei Zhou, Elynn Chen, and Yujun Yan

In Under Review, Conference on Neural Information Processing Systems (NeurIPS), 2026

Bib

@inproceedings{zhang2026optimize,
  stream = {decision},
  title = {Optimize Once, Execute Fast: Latency-Aware Multi-Agent Workflow Learning for Recurrent Queries},
  author = {Zhang, Enpei and Qu, Feiyu and Huang, Zheng and Zhou, Dawei and Chen, Elynn and Yan, Yujun},
  booktitle = {Under Review, Conference on Neural Information Processing Systems (NeurIPS)},
  year = {2026}
}

2025

ICAIF

Time-Varying Factor-Augmented Models for Volatility Forecasting

Duo Zhang, Jiayu Li, Junyi Mo, and Elynn Chen

In ACM International Conference on AI in Finance (ICAIF), 2025

DOI Bib

@inproceedings{zhang2025volatility,
  stream = {decision},
  title = {Time-Varying Factor-Augmented Models for Volatility Forecasting},
  author = {Zhang, Duo and Li, Jiayu and Mo, Junyi and Chen, Elynn},
  booktitle = {ACM International Conference on AI in Finance (ICAIF)},
  year = {2025},
  doi = {10.1145/3768292.3770407}
}

ICAIF

ACT-Tensor: Tensor Completion Framework for Financial Dataset Imputation

Junyi Mo, Jiayu Li, Duo Zhang, and Elynn Chen

In ACM International Conference on AI in Finance (ICAIF), 2025

DOI Bib

@inproceedings{mo2025acttensor,
  stream = {decision},
  title = {ACT-Tensor: Tensor Completion Framework for Financial Dataset Imputation},
  author = {Mo, Junyi and Li, Jiayu and Zhang, Duo and Chen, Elynn},
  booktitle = {ACM International Conference on AI in Finance (ICAIF)},
  year = {2025},
  doi = {10.1145/3768292.3770408}
}

ACM EC

Maximal Extractable Value in Batch Auctions

Mengqian Zhang, Yuhao Li, Xinyuan Sun, Elynn Chen, and Xi Chen

In ACM Conference on Economics and Computation (EC), 2025

DOI Bib

@inproceedings{zhang2025mev,
  stream = {decision},
  title = {Maximal Extractable Value in Batch Auctions},
  author = {Zhang, Mengqian and Li, Yuhao and Sun, Xinyuan and Chen, Elynn and Chen, Xi},
  booktitle = {ACM Conference on Economics and Computation (EC)},
  year = {2025},
  doi = {10.1145/3736252.3742581}
}

2023

DeFi

MEV Makes Everyone Happy under Greedy Sequencing Rule

Yuhao Li, Mengqian Zhang, Jichen Li, Elynn Chen, Xi Chen, and Xiaotie Deng

In Proceedings of the 2023 Workshop on Decentralized Finance and Security, pp. 9-15, 2023

DOI Bib

@inproceedings{li2023mev,
  stream = {decision},
  title = {MEV Makes Everyone Happy under Greedy Sequencing Rule},
  author = {Li, Yuhao and Zhang, Mengqian and Li, Jichen and Chen, Elynn and Chen, Xi and Deng, Xiaotie},
  booktitle = {Proceedings of the 2023 Workshop on Decentralized Finance and Security, pp. 9-15},
  year = {2023},
  doi = {10.1145/3605768.3623543}
}

2022

J. Data Sci.

Modeling Dynamic Transport Network with Low-Rank Matrix-variate Time Series: an Application to International Trade Flow

Elynn Chen and Rong Chen

Journal of Data Science, 2022

DOI Bib

@article{chen2022transport,
  stream = {decision},
  title = {Modeling Dynamic Transport Network with Low-Rank Matrix-variate Time Series: an Application to International Trade Flow},
  author = {Chen, Elynn and Chen, Rong},
  journal = {Journal of Data Science},
  year = {2022},
  doi = {10.6339/22-JDS1065}
}