Publications

Links provided in titles. The ones that I served as Corresponding Author are marked with star.

Preprints

33. N. Ning* VT-MRF-SPF: Variable Target Markov Random Field Scalable Particle Filter

32. H. Li and N. Ning* Stochastic Differential Equations Driven by G-Brownian Motion with Mean Reflections

31. B. Lin, L. Zou, M. Yang, B. Zhou, D. Mandal, J. Abedin, H. Cai and N. Ning Understanding Human-COVID-19 Dynamics using Geospatial Big Data: A Systematic Literature Review

30. H. Li and N. Ning* Doubly Reflected Backward SDEs Driven by G-Brownian Motions and Fully Nonlinear PDEs with Double Obstacles

29. N. Ning* Quantum Expander Mixing Lemma and its Converse

28. N. Ning and J. Wu, Well-posedness and propagation of chaos for McKean-Vlasov stochastic variational inequalities

27. H. Li and N. Ning* Propagation of chaos for doubly mean reflected BSDEs

26. B. Lin, Y. Dai (my PhD student), L. Zou and N. Ning* Statistical Machine Learning Meets High-Dimensional Spatiotemporal Challenges - A Case Study of COVID-19 Modeling

25. N. Ning* and J. Qiu, The mbsts package: Multivariate Bayesian Structural Time Series Models in R.

24. Z. Kuang and N. Ning* Subexponential growth of self-similar fragmentations

23.  N. Ning, J. Wu, and X. Xu, Solutions and Stochastic Averaging for Delay-path-dependent Stochastic Variational Inequalities in Infinite Dimensions.

22. N. Ning*, Convergence of Dirichlet Forms for MCMC Optimal Scaling with General Target Distributions on Large Graphs

Peer-Reviewed Journal Publications 

2022-Present Assistant Professor @TAMU

21. J. Li (my PhD student), E. Ionides*, A. King, M. Pascualand, and N. Ning* Inference on spatiotemporal dynamics for coupled biological populations, Journal of the Royal Society Interface, to appear.

20. N. Ning* and E. Ionides, Systemic Infinitesimal Over-dispersion on General Stochastic Graphical Models, Statistics and Computing, to appear.

19. B. Ning and N. Ning* Spike and Slab Bayesian Sparse Principal Component Analysis, Statistics and Computing, Vol 34, 118, 2024.

18. N. Ning, J. Wu and J. Zheng, One-Dimensional McKean-Vlasov Stochastic Variational Inequalities and Coupled BSDEs with Locally Holder Noise Coefficients, Stochastic Processes and their Applications, Vol. 171, 104315, 2024. 

17. E. Ionides, N. Ning and J. Wheeler (alphabetical order), An Iterated Block Particle Filter for Inference on Coupled Dynamic Systems with Shared and Unit-specific Parameters,  Statistica Sinica, Vol. 34, 1-22, 2024.

16. N. Ning*, Bayesian Feature Selection in Joint Quantile Time Series Analysis, Bayesian Analysis, 1-27, 2023.

15. N. Ning* and E. Ionides, Iterated Block Particle Filter for High-dimensional Parameter Learning: Beating the Curse of Dimensionality, Journal of Machine Learning Research, 24(82):1−76, 2023. 

14. N. Ning and J. Wu,  Multi-dimensional Path-dependent Forward-backward Stochastic Variational Inequalities, Set-Valued and Variational Analysis, 31, 2, 2023.

2019-2022 Postdoc training @Umich

13. N. Ning* and W. Liu, Reconstructibility of a General DNA Evolution Model, Discrete Mathematics, Vol. 345, Issue 6, 2022.

12. N. Ning*, E. Ionides and Y. Ritov, Scalable Monte Carlo Inference and Rescaled Local Asymptotic Normality, Bernoulli, Vol. 27, No. 4, 2532-2555, 2021.

11. W. Liu and N. Ning*, Phase Transition of the Reconstructability of a General Symmetric Model with Different In-community and Out-community Mutations on an Infinite Tree, SIAM Journal on Discrete Mathematics, 35(2), 1381–1417, 2021.

10. N. Ning and J. Wu, Well-posedness and Stability Analysis of Two Classes of Generalized Stochastic Volatility Models, SIAM Journal on Financial Mathematics, Vol. 12, No. 1, pp. 79–109, 2021.

9. K. Ding and N. Ning*, Markov Chain Approximation and Measure Change for Time-inhomogeneous Stochastic Processes, Applied Mathematics and Computation, Volume 392, 1 March 2021.

8. J. Qiu, R. Jammalamadaka and N. Ning*, Multivariate time series analysis from a Bayesian machine learning perspective, Annals of Mathematics and Artificial Intelligence, 88(10), pp 1061-1082, 2020.

2018-2019 Postdoc training @UW Seattle

7. J. Qiu, W. Liu and N. Ning*, The Evolution of Regional Innovation with Spatial Knowledge Spillover: Convergence or Divergence?, Networks and Spatial Economics, 20, pp 179-208, 2020.

6. W. Liu and N. Ning*, Information Reconstruction on an Infinite Tree for a $4\times 4$-state Asymmetric Model with Community Effects, Journal of Statistical Physics, Vol. 177, Issue 3, pp 438–467, 2019.

5. R. Jammalamadaka, J. Qiu and N. Ning*, Predicting a Stock Portfolio with the Multivariate Bayesian Structural Time Series Model: Do News or Emotions Matter?, International Journal of Artificial Intelligence, Vol. 17, Number 2, pp 81-104, 2019.

4. W. Liu and N. Ning*, Large Degree Asymptotics and the Reconstruction Threshold of the Asymmetric Binary Channels, Journal of Statistical Physics, Vol. 174, Issue 6, pp 1161–1188, 2019.

2014-2018 PhD study @UCSB

3. J. P. Fouque and N. Ning, Uncertain Volatility Models with Stochastic Bounds, SIAM Journal on Financial Mathematics, 9(4), 1175–1207, 2018.

2. W. Liu, R. Jammalamadaka and N. Ning, The Tightness of the Kesten-Stigum Reconstruction Bound of Symmetric Model with Multiple Mutations, Journal of Statistical Physics, Vol. 170, Issue 3, pp 617–641, 2018. 

1. J. Qiu, R. Jammalamadaka and N. Ning, Multivariate Bayesian Structural Time Series Model, Journal of Machine Learning Research, 19(68):1-33, 2018.