Manuscripts
To be Published Su, B., Collina, N. ,Wen, G., Li, D., Cho, K., Fan, J., Zhao, B., Su, W. (2026+). Manuscript. Li, G., Yan, Y.L., Chen, Y., and Fan, J. (2026+).Minimax-Optimal Reward-Agnostic Exploration in Reinforcement Learning .Mathematics of Operations Research , to appear. Bhattacharya, S., Fan, J., and Hou, J. (2026). Inferences on mixing probabilities and ranking in mixed-membership models. Manuscript. Bhattacharya, S., Fan, J., and Hou, J. (2026). Inferences on mixing probabilities and ranking in mixed-membership models. Manuscript. Fan, J., Li, Y., Xia, N., and Zheng, X. (2026+).Tests for principal eigenvalues and eigenvectors. Journal of the American Statistical Association , to appear. Ait-Sahalia, Y., Fan, J., Xue, L., and Zhu, X. (2025+). How and when are high-frequency prices predictable? Management Science, to appear. Under Review He, Y., Yin, Q., Cao, Y., Fan, J., Liu, H. (2026). A Theory on Flow Matching with Neural Networks. Gu, Y., Yin, Q., Cai, T., and Fan, J. (2026).Optimally taming biases in black-box models for efficient semiparametric estimation. Wu, Y., Wang, H., Li, R., Fan, J., and Chen, Y. (2026). Chai, J., Fan, J., Gao, C. and Yin, Q. (2026). SMART Fine-tuning Factor Augmented Neural Lasso for Heterogeneous Environments. Chai, J., Duan, Y., Fan, J., Wang, K. (2026).Optimal semiparametric dynamic pricing with feature diversity. Fan, J., Ke, Z.T., and Shi, Z (2026).Optimally Demixing of Nonparametric Densities. Chai, J., Fan, J., and Gu, Y. (2025).Neural distribution regression. Fan, J., Liu, Q., Pei, R., and Wang, Z. (2025). Let Tables Talk: Auditing and Enhancing Corporate Narratives with LLMs. Li, X., Gu, Y., and Fan, J. (2025).Optimal estimation of a factorizable density using diffusion models with ReLU Neural Networks. Dai, H., Fan, J., Gu, Y., and Murkherjee, D. (2025). CINDES: Classification induced neural density estimator and simulator. Fan, J., Kwon, H., and Zhu, X. (2025).Uncertainty quantification for ranking with heterogeneous preferences. Fan, J., Jana, S., Kulkarni, S. and Yin, Q. (2025). Factor Informed Double Deep Learning For Average Treatment Effect Estimation. Gu, Y., Fang, C., Xu, Y., Guo, Z., Fan, J. (2025). Fundamental Computational Limits in Pursuing Invariant Causal Prediction and Invariance-Guided Regularization . Fan, J., Ge, J., and Hou, J. (2025). Covariates-Adjusted Mixed-Membership Estimation: A Novel Network Model with Near-Optimal Guarantees. Wu, D., He, Y., Cao, Y., Fan, J., Liu, H. (2025). Transformers and Their Roles as Time Series Foundation Models . Cao, Y., He, Y., Wu, D., Chen, H.-Y, Fan, J., Liu, H. (2025). Transformers Simulate MLE for Sequence Generation in Bayesian Networks . He, Y., Cao, Y., Chen, H.Y., Wu, D., Fan, J., Liu, H. (2025). Learning Spectral Methods by Transformers . Chai, J., Chen, E.Y., Fan, J. (2025). Deep Transfer Q-Learning for Offline Non-Stationary Reinforcement Learning . Chai, J., Duan, Y., Fan, J., Wang, K. (2025). Localized exploration in contextual dynamic pricing achieves dimension-free regret. Manuscript. Jiang, S. and Fan, J. (2024). Optimal Parameter Estimation in Degree Corrected Mixed Membership Models. Tang, S., Jana, S., and Fan, J. (2024). Factor Adjusted Spectral Clustering for Mixture Models. Fan, J.,Wang, W., Zhao, Y. (2024). Conditional nonparametric variable screening via neural network factor regression. Manuscript . Fan, J., Liu, Q., Song, Y. and Wang, Z. (2024). Measuring Misinformation in Financial Markets . Manuscript. Fan, J., Hou, J., and Yu, M. (2024). Covariate Assisted Entity Ranking with Sparse Intrinsic Scores. Manuscript. Fan, J., Yan, Y., and Zheng, Y. (2024). When can weak latent factors be statistically inferred? Manuscript. Li, X., He, Y., Liu, H., Fan, J. (2024). Liu, W., Xu, G., Fan, J., and Zhu, X. (2024). Fan, J., Wang, Z., Yang, Z., Ye, C. (2023).Provably Efficient High-Dimensional Bandit Learning with Batched Feedbacks . Fan, J., Tong, X., Wu, Y., Xia, L., and Yao, S. (2023).Neyman-Pearson and equal opportunity: when efficiency meets fairness in classification. He, Y., Liu, H., and Fan, J. (2023).Hidden Clique Inference in Random Ising Model II: the planted Sherrington-Kirkpatrick model. He, Y., Liu, H., and Fan, J. (2023).Hidden Clique Inference in Random Ising Model I: the planted random field Curie-Weiss model. Giessing, A. and Fan, J. (2023). A Bootstrap Hypothesis Test for High-Dimensional Mean Vectors. Fan, J., Ge, J., and Mukherjee, D. (2023).UTOPIA: Universally Trainable Optimal Prediction Intervals Aggregation. Fan, J., Fan, Y., Lv, J., and Yang, F. (2022). SIMPLE-RC: Group Network Inference with Non-Sharp Nulls and Weak Signals. Manuscript . Bayle, P. and Fan, J. (2022). Factor-Augmented Regularized Model for Hazard Regression. Manuscript . Yu, M., Yang, Z., and Fan, J. (2022).Strategic Decision-Making in the Presence of Information Asymmetry: Provably Efficient RL with Algorithmic Instruments. Manuscript . Fan, J., Ke, Z., Liao, Y., and Neuhierl (2022).Structural Deep Learning in Conditional Asset Pricing. Manuscript . Fan, J., Guo, Y., and Zhu, Z. (2020). When is best subset selection the ``best''? Manuscript . Giessing, A. and Fan, J. (2020). Bootstrapping $\ell_p$-statistics in high dimensions. Manuscript . Fan, J., Wang, Z., Xie, Y., and Yang, Z. (2020). A Theoretical Analysis of Deep Q-Learning. Manuscript . Fan, J., Weng, H. and Zhou, Y. (2019). Optimal estimation of functionals of high-dimensional mean and covariance matrix. Manuscript . Fan, J., Liu, H., Wang, Z. and Yang, Z. (2018). Curse of Heterogeneity: Computational Barriers in Sparse Mixture Models and Phase Retrieval. Manuscript . Balasubramanian, K., Fan, J., and Yang, Z. (2018).Tensor methods for additive index models under discordance and heterogeneity. Manuscript. Fan, J. and Zhong, Y. (2018). Optimal subspace estimation using overidentifying vectors via generalized method of moments. Manuscript.
Back to
Top
