An S-Plus function to calculate relative risks and adjusted means for regression models using natural splines. - Jiguo Cao; Marie-France Valois; Mark S. Goldberg (Comput. Methods Programs Biomed., 2006)

Parameter cascades and profiling in functional data analysis. - Jiguo Cao; James O. Ramsay (Comput. Stat., 2007)

Estimating dynamic models for gene regulation networks. - Jiguo Cao; Hongyu Zhao 003 (Bioinform., 2008)

Generalized profiling estimation for global and adaptive penalized spline smoothing. - Jiguo Cao; James O. Ramsay (Comput. Stat. Data Anal., 2009)

Signal Classification Using Random Forest with Kernels. - Jiguo Cao; Guangzhe Fan (AICT, 2010)

Functional data classification for temporal gene expression data with kernel-induced random forests. - Guangzhe Fan; Jiguo Cao; Jiheng Wang (CIBCB, 2010)

Automated Load Curve Data Cleansing in Power Systems. - Jiyi Chen; Wenyuan Li; Adriel Lau; Jiguo Cao; Ke Wang (IEEE Trans. Smart Grid, 2010)

Systems mapping: how to improve the genetic mapping of complex traits through design principles of biological systems. - Rongling Wu; Jiguo Cao; Zhongwen Huang; Zhong Wang 001; Junyi Gai; C. Eduardo Vallejos (BMC Syst. Biol., 2011)

Blockwise empirical likelihood for time series of counts. - Rongning Wu; Jiguo Cao (J. Multivar. Anal., 2011)

Estimating generalized semiparametric additive models using parameter cascading. - Jiguo Cao (Stat. Comput., 2012)

Estimating curves and derivatives with parametric penalized spline smoothing. - Jiguo Cao; Jing Cai; Liangliang Wang (Stat. Comput., 2012)

Estimating mixed-effects differential equation models. - L. Wang; Jiguo Cao; James O. Ramsay; D. M. Burger; C. J. L. Laporte; Jürgen K. Rockstroh (Stat. Comput., 2014)

Fitting a Stochastic Model to Eye Movement Time Series in a Categorization Task. - Paul F. Tupper; Thuan Pham Nguyen; Yunlong Nie; Jiguo Cao; Liangliang Wang (CogSci, 2017)

Estimating functional linear mixed-effects regression models. - Baisen Liu; Liangliang Wang; Jiguo Cao (Comput. Stat. Data Anal., 2017)

Sparse estimation for functional semiparametric additive models. - Peijun Sang; Richard A. Lockhart; Jiguo Cao (J. Multivar. Anal., 2018)

Bayesian estimation of ordinary differential equation models when the likelihood has multiple local modes. - Baisen Liu; Liangliang Wang; Jiguo Cao (Monte Carlo Methods Appl., 2018)

Supervised functional principal component analysis. - Yunlong Nie; Liangliang Wang; Baisen Liu; Jiguo Cao (Stat. Comput., 2018)

Bayesian inference of mixed-effects ordinary differential equations models using heavy-tailed distributions. - Baisen Liu; Liangliang Wang; Yunlong Nie; Jiguo Cao (Comput. Stat. Data Anal., 2019)

Weighted empirical likelihood inference for dynamical correlations. - Peijun Sang; Liangliang Wang; Jiguo Cao (Comput. Stat. Data Anal., 2019)

FuncNN: An R Package to Fit Deep Neural Networks Using Generalized Input Spaces. - Barinder Thind; Sidi Wu; Richard Groenewald; Jiguo Cao (CoRR, 2020)

Neural Networks as Functional Classifiers. - Barinder Thind; Kevin Multani; Jiguo Cao (CoRR, 2020)

Sparse functional principal component analysis in a new regression framework. - Yunlong Nie; Jiguo Cao (Comput. Stat. Data Anal., 2020)

Functional single-index quantile regression models. - Peijun Sang; Jiguo Cao (Stat. Comput., 2020)

Estimating time-varying directed neural networks. - Haixu Wang; Jiguo Cao (Stat. Comput., 2020)

Appointment scheduling with a quantile objective. - Peijun Sang; Mehmet A. Begen; Jiguo Cao (Comput. Oper. Res., 2021)

Machine Learning Based Multimodal Neuroimaging Genomics Dementia Score for Predicting Future Conversion to Alzheimer's Disease. - Ghazal Mirabnahrazam; Da Ma; Sieun Lee; Karteek Popuri; Hyunwoo Lee 007; Jiguo Cao; Lei Wang; James E. Galvin; Mirza Faisal Beg; Alzheimer's Disease Neuroimaging Initiative (CoRR, 2022)

Predicting Time-to-conversion for Dementia of Alzheimer's Type using Multi-modal Deep Survival Analysis. - Ghazal Mirabnahrazam; Da Ma; Cédric Beaulac; Sieun Lee; Karteek Popuri; Hyunwoo Lee 007; Jiguo Cao; James E. Galvin; Lei Wang; Mirza Faisal Beg; Alzheimer's Disease Neuroimaging Initiative (CoRR, 2022)

Dynamical modeling for non-Gaussian data with high-dimensional sparse ordinary differential equations. - Muye Nanshan; Nan Zhang 020; Xiaolei Xun; Jiguo Cao (Comput. Stat. Data Anal., 2022)

Sparse functional partial least squares regression with a locally sparse slope function. - Tianyu Guan; Zhenhua Lin; Kevin Groves; Jiguo Cao (Stat. Comput., 2022)

A Joint estimation approach to sparse additive ordinary differential equations. - Nan Zhang 020; Muye Nanshan; Jiguo Cao (Stat. Comput., 2022)

Two-Dimensional Functional Principal Component Analysis for Image Feature Extraction. - Haolun Shi; Yuping Yang; Liangliang Wang; Da Ma; Mirza Faisal Beg; Jian Pei 001; Jiguo Cao (J. Comput. Graph. Stat., 2022)

Functional L-Optimality Subsampling for Functional Generalized Linear Models with Massive Data. - Hua Liu; Jinhong You; Jiguo Cao (J. Mach. Learn. Res., 2023)

Automatic search intervals for the smoothing parameter in penalized splines. - Zheyuan Li; Jiguo Cao (Stat. Comput., 2023)

Deep Learning With Functional Inputs. - Barinder Thind; Kevin Multani; Jiguo Cao (J. Comput. Graph. Stat., 2023)

pCODE: Estimating Parameters of ODE Models. - Haixu Wang; Jiguo Cao (R J., 2023)

Unsupervised learning on U.S. weather forecast performance. - Chuyuan Lin; Ying Yu; Lucas Y. Wu; Jiguo Cao (Comput. Stat., 2023)

Neural networks for scalar input and functional output. - Sidi Wu; Cédric Beaulac; Jiguo Cao (Stat. Comput., 2023)

Cost-Sensitive Learning for Medical Insurance Fraud Detection With Temporal Information. - Haolun Shi; Mohammad A. Tayebi; Jian Pei 001; Jiguo Cao (IEEE Trans. Knowl. Data Eng., 2023)

Neuroimaging feature extraction using a neural network classifier for imaging genetics. - Cédric Beaulac; Sidi Wu; Erin Gibson; Michelle F. Miranda; Jiguo Cao; Leno Rocha; Mirza Faisal Beg; Farouk S. Nathoo (BMC Bioinform., 2023)

Representation learning of dynamic networks. - Haixu Wang; Jiguo Cao; Jian Pei 001 (CoRR, 2024)

Dynamic Survival Prediction Using Sparse Longitudinal Images via Multi-Dimensional Functional Principal Component Analysis. - Haolun Shi; Shu Jiang; Da Ma; Mirza Faisal Beg; Jiguo Cao (J. Comput. Graph. Stat., 2024)

Functional Nonlinear Learning. - Haixu Wang; Jiguo Cao (J. Comput. Graph. Stat., 2024)

Functional autoencoder for smoothing and representation learning. - Sidi Wu; Cédric Beaulac; Jiguo Cao (Stat. Comput., 2024)

Optimal subsampling for generalized additive models on large-scale datasets. - Lili Li; Bingfan Liu; Xiaodi Liu; Haolun Shi; Jiguo Cao (Stat. Comput., 2025)

Probabilistic Functional Neural Networks. - Haixu Wang; Jiguo Cao (CoRR, 2025)

Robust Bayesian functional principal component analysis. - Jiarui Zhang; Jiguo Cao; Liangliang Wang (Stat. Comput., 2025)