2 citations · 4 across the 8 of their papers we have counts for
9 papers
Functional Autoencoders for Amplitude-Phase Representation Learning
Peida Wu, Xinyang Xiong, Pengcheng Zeng
Functional data are intrinsically infinite-dimensional, and often exhibit phase variation, where corresponding events occur at different times across observations. Existing linear…
NeuralFLoC: Neural Flow-Based Joint Registration and Clustering of Functional Data
Xinyang Xiong, Siyuan jiang, Pengcheng Zeng
Clustering functional data in the presence of phase variation is challenging, as temporal misalignment can obscure intrinsic shape differences and degrade clustering performance. M…
Adaptively Truncated Signature-based Logistic Regression for Semi-parametric Functional Classification
Pengcheng Zeng, Siyuan Jiang
Modern sensing technologies routinely generate multi-dimensional functional data, often accompanied by scalar covariates, motivating statistical methods that can jointly accommodat…
DeepFRC: An End-to-End Deep Learning Model for Functional Registration and Classification
Siyuan Jiang, Yihan Hu, Wenjie Li +1
Functional data, representing curves or trajectories, are ubiquitous in fields like biomedicine and motion analysis. A fundamental challenge is phase variability -- temporal misali…
Similarity-driven and Task-driven Models for Diversity of Opinion in Crowdsourcing Markets
Chen Jason Zhang, Yunrui Liu, Pengcheng Zeng +4
The recent boom in crowdsourcing has opened up a new avenue for utilizing human intelligence in the realm of data analysis. This innovative approach provides a powerful means for c…
scICML: Information-theoretic Co-clustering-based Multi-view Learning for the Integrative Analysis of Single-cell Multi-omics data
Pengcheng Zeng, Zhixiang Lin
Modern high-throughput sequencing technologies have enabled us to profile multiple molecular modalities from the same single cell, providing unprecedented opportunities to assay ce…
Joint Curve Registration and Classification with Two-level Functional Models
Lin Tang, Pengcheng Zeng, Jian Qing Shi +1
Many classification techniques when the data are curves or functions have been recently proposed. However, the presence of misaligned problems in the curves can influence the perfo…
Elastic Coupled Co-clustering for Single-Cell Genomic Data
Pengcheng Zeng, Zhixiang Lin
The recent advances in single-cell technologies have enabled us to profile genomic features at unprecedented resolution and datasets from multiple domains are available, including…
Simultaneous Registration and Clustering for Multi-dimensional Functional Data
Pengcheng Zeng, Jian Qing Shi, Won-Seok Kim
The clustering for functional data with misaligned problems has drawn much attention in the last decade. Most methods do the clustering after those functional data being registered…