Jian Kang
30 catalog papers. Identity-linked publications and additional name matches are distinguished below.
ORCID: 0000-0002-5643-2668
University of Michigan
Publications
- Bayesian Signal Matching for Transfer Learning in ERP-Based Brain Computer Interface — Journal of the American Statistical Association 2026
- Latent class analysis with discrete failure time model — The Annals of Applied Statistics 2026 (name-matched, not ORCID-linked)
- Bayesian image-on-image regression via deep kernel learning based Gaussian processes — The Annals of Applied Statistics 2026 (name-matched, not ORCID-linked)
- A Bayesian reinforcement learning framework for optimizing the BCI-utility of P300 brain-computer interfaces — The Annals of Applied Statistics 2026
- Scalable Bayesian inference for heat kernel Gaussian processes on manifolds — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2026
- Bayesian Image Mediation Analysis — Journal of the American Statistical Association 2026
- Bayesian Inference on Brain-Computer Interfaces via GLASS — Journal of the American Statistical Association 2025
- Bayesian Scalar-on-Image Regression with a Spatially Varying Single-layer Neural Network Prior — Journal of Machine Learning Research 2025 (name-matched, not ORCID-linked)
- Robust High-Dimensional Regression with Coefficient Thresholding and Its Application to Imaging Data Analysis — Journal of the American Statistical Association 2024
- Composite scores for transplant center evaluation: A new individualized empirical null method — The Annals of Applied Statistics 2024
- Bayesian Spatial Blind Source Separation via the Thresholded Gaussian Process — Journal of the American Statistical Association 2024
- Statistical Inferences for Complex Dependence of Multimodal Imaging Data — Journal of the American Statistical Association 2024
- Latent subgroup identification in image-on-scalar regression — The Annals of Applied Statistics 2024
- Individualized risk assessment of preoperative opioid use by interpretable neural network regression — The Annals of Applied Statistics 2023
- Bayesian learning of Covid-19 vaccine safety while incorporating adverse events ontology — The Annals of Applied Statistics 2023 (name-matched, not ORCID-linked)
- Discussion of “LESA: Longitudinal Elastic Shape Analysis of Brain Subcortical Structures” — Journal of the American Statistical Association 2023
- Image response regression via deep neural networks — Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2023
- Bayesian inference for brain activity from functional magnetic resonance imaging collected at two spatial resolutions — The Annals of Applied Statistics 2022
- Bayesian Inferences on Neural Activity in EEG-Based Brain-Computer Interface — Journal of the American Statistical Association 2022
- Scalar on network regression via boosting — The Annals of Applied Statistics 2022
- Scalar-on-image regression via the soft-thresholded Gaussian process — Biometrika 2018
- Partition-based ultrahigh-dimensional variable screening — Biometrika 2017
- Discussion of “Fiber direction estimation in diffusion MRI” — The Annals of Applied Statistics 2016
- A Bayesian hierarchical spatial point process model for multi-type neuroimaging meta-analysis — The Annals of Applied Statistics 2014
- A Bayesian nonparametric mixture model for selecting genes and gene subnetworks — The Annals of Applied Statistics 2014
- Meta Analysis of Functional Neuroimaging Data via Bayesian Spatial Point Processes — Journal of the American Statistical Association 2011
- Scalable Bayesian Image-on-Scalar Regression for Population-Scale Neuroimaging Data Analysis — Journal of the American Statistical Association
- Statistical Inference for Mediation Models with High Dimensional Exposures and Mediators — Journal of the American Statistical Association
- Development of Public Health Policy by Digital Twin Microsimulation and Q-learning: A COVID-19 Booster Case Study — Journal of the American Statistical Association
- “Rebuilding” Statistics in the Age of AI: Culture, Infrastructure, and Training — Journal of the American Statistical Association