Jane-Ling Wang

According to our database, Jane-Ling Wang authored at least 16 papers between 2009 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Detecting Errors in Numerical Data via any Regression Model.

Hang Zhou, Jonas Mueller, Mayank Kumar, Jane-Ling Wang, Jing Lei

CoRR, 2023

2022

Eigen-Adjusted Functional Principal Component Analysis.

Ci-Ren Jiang, Eardi Lila, John A. D. Aston, Jane-Ling Wang

J. Comput. Graph. Stat., October, 2022

2021

Modeling sparse longitudinal data in early neurodevelopment.

Yaqing Chen, Paromita Dubey, Hans-Georg Müller, Muriel Bruchhage, Jane-Ling Wang, Sean C. L. Deoni

NeuroImage, 2021

Deep Extended Hazard Models for Survival Analysis.

Qixian Zhong, Jonas Mueller, Jane-Ling Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Learning for Functional Data Analysis with Adaptive Basis Layers.

Junwen Yao, Jonas Mueller, Jane-Ling Wang

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Emotional EEG classification using connectivity features and convolutional neural networks.

Seong-Eun Moon, Chun-Jui Chen, Cho-Jui Hsieh, Jane-Ling Wang, Jong-Seok Lee

Neural Networks, 2020

Greedy Attack and Gumbel Attack: Generating Adversarial Examples for Discrete Data.

Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, Michael I. Jordan

J. Mach. Learn. Res., 2020

A new approach to varying-coefficient additive models with longitudinal covariates.

Xiaoke Zhang, Qixian Zhong, Jane-Ling Wang

Comput. Stat. Data Anal., 2020

ML-LOO: Detecting Adversarial Examples with Feature Attribution.

Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, Michael I. Jordan

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Editorial for the special issue on High-dimensional and functional data analysis.

Frédéric Ferraty, Piotr Kokoszka, Jane-Ling Wang, Yichao Wu

Comput. Stat. Data Anal., 2019

A New Approach for Functional Connectivity via Alignment of Blood Oxygen Level-Dependent Signals.

Chun-Jui Chen, Jane-Ling Wang

Brain Connect., 2019

2018

Local and global temporal correlations for longitudinal data.

Yang Zhou, Shu-Chin Lin, Jane-Ling Wang

J. Multivar. Anal., 2018

2014

FMEM: Functional mixed effects modeling for the analysis of longitudinal white matter Tract data.

Ying Yuan, John H. Gilmore, Xiujuan Geng, Martin Andreas Styner, Kehui Chen, Jane-Ling Wang, Hongtu Zhu

NeuroImage, 2014

Spontaneous Neural Fluctuations Predict Decisions to Attend.

Jesse J. Bengson, Todd A. Kelley, Xiaoke Zhang, Jane-Ling Wang, George R. Mangun

J. Cogn. Neurosci., 2014

2013

A Longitudinal Functional Analysis Framework for Analysis of White Matter Tract Statistics.

Ying Yuan, John H. Gilmore, Xiujuan Geng, Martin Andreas Styner, Kehui Chen, Jane-Ling Wang, Hongtu Zhu

Proceedings of the Information Processing in Medical Imaging, 2013

2009

Smoothing dynamic positron emission tomography time courses using functional principal components.

Ci-Ren Jiang, John A. D. Aston, Jane-Ling Wang

NeuroImage, 2009