A new look at state-space models for neural data. - Liam Paninski; Yashar Ahmadian; Daniel Gil Ferreira; Shinsuke Koyama; Kamiar Rahnama Rad; Michael Vidne; Joshua T. Vogelstein; Wei Wu 006 (J. Comput. Neurosci., 2010)

Signal Estimation Under Random Time-Warpings and Nonlinear Signal Alignment. - Sebastian Kurtek; Anuj Srivastava; Wei Wu 006 (NIPS, 2011)

An information-geometric framework for statistical inferences in the neural spike train space. - Wei Wu 006; Anuj Srivastava (J. Comput. Neurosci., 2011)

Estimation of a mean template from spike-train data. - Wei Wu 006; Anuj Srivastava (EMBC, 2012)

Coupling time decoding and trajectory decoding using a target-included model in the motor cortex. - Vernon Lawhern; Nicholas G. Hatsopoulos; Wei Wu 006 (Neurocomputing, 2012)

An efficient multiple protein structure comparison method and its application to structure clustering and outlier detection. - Wei Wu 006; Anuj Srivastava; Jose Laborde; Jinfeng Zhang (BIBM, 2013)

Generative models for functional data using phase and amplitude separation. - J. Derek Tucker; Wei Wu 006; Anuj Srivastava (Comput. Stat. Data Anal., 2013)

Estimating summary statistics in the spike-train space. - Wei Wu 006; Anuj Srivastava (J. Comput. Neurosci., 2013)

Modeling and Analysis of Neural Spike Trains. - Wei Wu 006; Asohan Amarasingham; Zhe (Sage) Chen; Sung-Phil Kim (Comput. Intell. Neurosci., 2014)

SRSF shape analysis for sequencing data reveal new differentiating patterns. - Sergiusz Wesolowski; Daniel Vera; Wei Wu 006 (Comput. Biol. Chem., 2017)

Elastic Handling of Predictor Phase in Functional Regression Models. - Kyungmin Ahn; J. Derek Tucker; Wei Wu 006; Anuj Srivastava (CVPR Workshops, 2018)

Robust template estimation for functional data with phase variability using band depth. - Jason Cleveland; Weilong Zhao; Wei Wu 006 (Comput. Stat. Data Anal., 2018)

Regression models using shapes of functions as predictors. - Kyungmin Ahn; J. Derek Tucker; Wei Wu 006; Anuj Srivastava (Comput. Stat. Data Anal., 2020)

Intensity Estimation for Poisson Process With Compositional Noise. - Glenna Schluck; Wei Wu 006; Anuj Srivastava (Frontiers Appl. Math. Stat., 2021)

A reinforcement learning approach for protein-ligand binding pose prediction. - Chenran Wang; Yang Chen; Yuan Zhang; Keqiao Li; Menghan Lin; Feng Pan; Wei Wu 006; Jinfeng Zhang (BMC Bioinform., 2022)

Data-Driven, Soft Alignment of Functional Data Using Shapes and Landmarks. - Xiaoyang Guo; Wei Wu 006; Anuj Srivastava (CoRR, 2022)

A unified framework on defining depth for point process using function smoothing. - Zishen Xu; Chenran Wang; Wei Wu 006 (Comput. Stat. Data Anal., 2022)

Rank-Based Mixture Models for Temporal Point Processes. - Yang Chen; Yijia Ma; Wei Wu 006 (Frontiers Appl. Math. Stat., 2022)

Statistical depth for point process via the isometric log-ratio transformation. - Xinyu Zhou; Yijia Ma; Wei Wu 006 (Comput. Stat. Data Anal., 2023)

A stochastic process representation for time warping functions. - Yijia Ma; Xinyu Zhou; Wei Wu 006 (Comput. Stat. Data Anal., 2024)

A novel point process model for neuronal spike trains. - Yijia Ma; Wei Wu 006 (Frontiers Appl. Math. Stat., 2024)