Wenxin Jiang

Publication Activity (10 Years)

Years Active: 1998-2024
Publications (10 Years): 34

Top Topics

High Dimensional

Interaction Networks

Top Venues

Eng. Appl. Artif. Intell.

PLoS Comput. Biol.

Publications

Yutong Dong, Hongkai Jiang, Wenxin Jiang, Lianbing Xie
Dynamic normalization supervised contrastive network with multiscale compound attention mechanism for gearbox imbalanced fault diagnosis. Eng. Appl. Artif. Intell. 133 (2024)
Renhe Yao, Hongkai Jiang, Wenxin Jiang, Yunpeng Liu, Yutong Dong
Deep discriminative sparse representation learning for machinery fault diagnosis. Eng. Appl. Artif. Intell. 135 (2024)
Wenxin Jiang, Jerin Yasmin, Jason Jones, Nicholas Synovic, Jiashen Kuo, Nathaniel Bielanski, Yuan Tian, George K. Thiruvathukal, James C. Davis
PeaTMOSS: A Dataset and Initial Analysis of Pre-Trained Models in Open-Source Software. CoRR (2024)
Yutong Dong, Hongkai Jiang, Xin Wang, Mingzhe Mu, Wenxin Jiang
An interpretable multiscale lifting wavelet contrast network for planetary gearbox fault diagnosis with small samples. Reliab. Eng. Syst. Saf. 251 (2024)
Purvish Jajal, Wenxin Jiang, Arav Tewari, Joseph Woo, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis
Analysis of Failures and Risks in Deep Learning Model Converters: A Case Study in the ONNX Ecosystem. CoRR (2023)
Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. ICSE (2023)
Wenxin Jiang, Jason Jones, Jerin Yasmin, Nicholas Synovic, Rajeev Sashti, Sophie Chen, George K. Thiruvathukal, Yuan Tian, James C. Davis
PeaTMOSS: Mining Pre-Trained Models in Open-Source Software. CoRR (2023)
James C. Davis, Purvish Jajal, Wenxin Jiang, Taylor R. Schorlemmer, Nicholas Synovic, George K. Thiruvathukal
Reusing Deep Learning Models: Challenges and Directions in Software Engineering. JVA (2023)
Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Guo, Wenxin Jiang, James C. Davis
Discrepancies among Pre-trained Deep Neural Networks: A New Threat to Model Zoo Reliability. CoRR (2023)
Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages. CoRR (2023)
Wenxin Jiang, Chingwo Cheung, George K. Thiruvathukal, James C. Davis
Exploring Naming Conventions (and Defects) of Pre-trained Deep Learning Models in Hugging Face and Other Model Hubs. CoRR (2023)
Wenxin Jiang, Nicholas Synovic, Purvish Jajal, Taylor R. Schorlemmer, Arav Tewari, Bhavesh Pareek, George K. Thiruvathukal, James C. Davis
PTMTorrent: A Dataset for Mining Open-source Pre-trained Model Packages. MSR (2023)
Wenxin Jiang, Nicholas Synovic, Matt Hyatt, Taylor R. Schorlemmer, Rohan Sethi, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis
An Empirical Study of Pre-Trained Model Reuse in the Hugging Face Deep Learning Model Registry. CoRR (2023)
Wenxin Jiang, Vishnu Banna, Naveen Vivek, Abhinav Goel, Nicholas Synovic, George K. Thiruvathukal, James C. Davis
Challenges and Practices of Deep Learning Model Reengineering: A Case Study on Computer Vision. CoRR (2023)
Jakob Veselsky, Jack West, Isaac Ahlgren, George K. Thiruvathukal, Neil Klingensmith, Abhinav Goel, Wenxin Jiang, James C. Davis, Kyuin Lee, Younghyun Kim
Establishing trust in vehicle-to-vehicle coordination: a sensor fusion approach. HotMobile (2022)
Diego Montes, Pongpatapee Peerapatanapokin, Jeff Schultz, Chengjun Guo, Wenxin Jiang, James C. Davis
Discrepancies among pre-trained deep neural networks: a new threat to model zoo reliability. ESEC/SIGSOFT FSE (2022)
Nicholas Synovic, Matt Hyatt, Rohan Sethi, Sohini Thota, Shilpika, Allan J. Miller, Wenxin Jiang, Emmanuel S. Amobi, Austin Pinderski, Konstantin Läufer, Nicholas J. Hayward, Neil Klingensmith, James C. Davis, George K. Thiruvathukal
Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics. CoRR (2022)
Wenxin Jiang, Nicholas Synovic, Rohan Sethi, Aryan Indarapu, Matt Hyatt, Taylor R. Schorlemmer, George K. Thiruvathukal, James C. Davis
An Empirical Study of Artifacts and Security Risks in the Pre-trained Model Supply Chain. SCORED@CCS (2022)
Wenxin Jiang, Guochang Zhu, Yiyun Shen, Qian Xie, Min Ji, Yongtao Yu
An Empirical Mode Decomposition Fuzzy Forecast Model for Air Quality. Entropy 24 (12) (2022)
Wenxin Jiang, Bolun Chen, Zifan Qi, Yongtao Yu
Link Prediction Based on Sampled Single Vertices. ICAIS (1) (2022)
Nicholas M. Synovic, Matt Hyatt, Rohan Sethi, Sohini Thota, Shilpika, Allan J. Miller, Wenxin Jiang, Emmanuel S. Amobi, Austin Pinderski, Konstantin Läufer, Nicholas J. Hayward, Neil Klingensmith, James C. Davis, George K. Thiruvathukal
Snapshot Metrics Are Not Enough: Analyzing Software Repositories with Longitudinal Metrics. ASE (2022)
Haiyang Li, Wenxin Jiang, Jin Deng, Ruien Yu, Qianghua Pan
A Sensitive Frequency Range Method Based on Laser Ultrasounds for Micro-Crack Depth Determination. Sensors 22 (19) (2022)
Wenxin Jiang
Research on the construction and application of College Ideology network system based on Data Mining. ICISCAE (ACM) (2021)
Yang Xu, Hongmei Jiang, Wenxin Jiang
Extended graphical lasso for multiple interaction networks for high dimensional omics data. PLoS Comput. Biol. 17 (10) (2021)
Wei Ju, Wenxin Jiang
A Note on Comparison of F-measures. CoRR (2021)
Vishnu Banna, Akhil Chinnakotla, Zhengxin Yan, Anirudh Vegesana, Naveen Vivek, Kruthi Krishnappa, Wenxin Jiang, Yung-Hsiang Lu, George K. Thiruvathukal, James C. Davis
An Experience Report on Machine Learning Reproducibility: Guidance for Practitioners and TensorFlow Model Garden Contributors. CoRR (2021)
Wenxin Jiang
Statistical Formulas for F Measures. CoRR (2020)
Yang Yu, Ning Zhang, Daniel W. Apley, Wenxin Jiang
Including a Nugget Effect in Lifted Brownian Covariance Models. SIAM/ASA J. Uncertain. Quantification 8 (4) (2020)
Ruimin Zhu, Thanapon Noraset, Alisa Liu, Wenxin Jiang, Doug Downey
Multi-sense Definition Modeling using Word Sense Decompositions. CoRR (2019)
Phu Van, Wenxin Jiang, Raphael Gottardo, Greg Finak
ggCyto: next generation open-source visualization software for cytometry. Bioinform. 34 (22) (2018)
Ruimin Zhu, Wenxin Jiang
Bayesian Complex Network Community Detection Using Nonparametric Topic Model. COMPLEX NETWORKS (1) (2018)
Grace Yoon, Yinan Zheng, Zhou Zhang, Haixiang Zhang, Tao Gao, Brian Joyce, Wei Zhang, Weihua Guan, Andrea A. Baccarelli, Wenxin Jiang, Joel Schwartz, Pantel Vokonas, Lifang Hou, Lei Liu
Ultra-high dimensional variable selection with application to normative aging study: DNA methylation and metabolic syndrome. BMC Bioinform. 18 (1) (2017)
Cheng Li, Wenxin Jiang
On oracle property and asymptotic validity of Bayesian generalized method of moments. J. Multivar. Anal. 145 (2016)
Yi Gao, Wenxin Jiang, Martin A. Tanner
Generalized Gini Correlation and its Application in Data-Mining. Data Min. Knowl. Discov. 30 (6) (2016)
Greg Finak, Jacob Frelinger, Wenxin Jiang, Evan W. Newell, John Ramey, Mark M. Davis, Spyros A. Kalams, Stephen C. De Rosa, Raphael Gottardo
OpenCyto: An Open Source Infrastructure for Scalable, Robust, Reproducible, and Automated, End-to-End Flow Cytometry Data Analysis. PLoS Comput. Biol. 10 (8) (2014)
Cheng Li, Wenxin Jiang, Martin A. Tanner
General Oracle Inequalities for Gibbs Posterior with Application to Ranking. COLT (2013)
Wenxin Jiang, Zbigniew W. Ras
Multi-label automatic indexing of music by cascade classifiers. Web Intell. Agent Syst. 11 (2) (2013)
Wenxin Jiang, Martin A. Tanner
Hierarchical Mixtures-of-Experts for Exponential Family Regression Models with Generalized Linear Mean Functions: A Survey of Approximation and Consistency Results CoRR (2013)
Eduardo F. Mendes, Wenxin Jiang
On Convergence Rates of Mixtures of Polynomial Experts. Neural Comput. 24 (11) (2012)
Greg Finak, Wenxin Jiang, Jorge Pardo, Adam Asare, Raphael Gottardo
QUAliFiER: An automated pipeline for quality assessment of gated flow cytometry data. BMC Bioinform. 13 (2012)
Lili Yao, Wenxin Jiang, Martin A. Tanner
Predicting Panel Data Binary Choice with the Gibbs Posterior. Neural Comput. 23 (10) (2011)
Bozena Kostek, Adam Kupryjanow, Pawel Zwan, Wenxin Jiang, Zbigniew W. Ras, Marcin Wojnarski, Joanna Swietlicka
Report of the ISMIS 2011 Contest: Music Information Retrieval. ISMIS (2011)
Cynthia Xin Zhang, Wenxin Jiang, Zbigniew W. Ras, Rory A. Lewis
Blind Music Timbre Source Isolation by Multi- resolution Comparison of Spectrum Signatures. RSCTC (2010)
Wenxin Jiang
On Uniform Deviations of General Empirical Risks with Unboundedness, Dependence, and High Dimensionality. J. Mach. Learn. Res. 10 (2009)
Rory A. Lewis, Wenxin Jiang, Zbigniew W. Ras
Mining Scalar Representations in a Non-tagged Music Database. ISMIS (2008)
Cynthia Xin Zhang, Wenxin Jiang, Zbigniew W. Ras
Harmonic Blind Sound Source Isolation Enhanced by Spectrum Clustering. ICDM Workshops (2008)
Rory A. Lewis, Amanda Cohen, Wenxin Jiang, Zbigniew W. Ras
Hierarchical Tree for Dissemination of Polyphonic Noise. RSCTC (2008)
Pamela L. Thompson, Cynthia Xin Zhang, Wenxin Jiang, Zbigniew W. Ras
From Mining Tinnitus Database to Tinnitus Decision-Support System, Initial Study. IAT (2007)
Yang Ge, Wenxin Jiang
A note on mixtures of experts for multiclass responses: approximation rate and Consistent Bayesian Inference. ICML (2006)
Wenxin Jiang
On the Consistency of Bayesian Variable Selection for High Dimensional Binary Regression and Classification. Neural Comput. 18 (11) (2006)
Yang Ge, Wenxin Jiang
On Consistency of Bayesian Inference with Mixtures of Logistic Regression. Neural Comput. 18 (1) (2006)
Wenxin Jiang
Boosting with Noisy Data: Some Views from Statistical Theory. Neural Comput. 16 (4) (2004)
Robert A. Jacobs, Wenxin Jiang, Martin A. Tanner
Factorial Hidden Markov Models and the Generalized Backfitting Algorithm. Neural Comput. 14 (10) (2002)
Wenxin Jiang
Some Theoretical Aspects of Boosting in the Presence of Noisy Data. ICML (2001)
Wenxin Jiang
Is regularization unnecessary for boosting?. AISTATS (2001)
Wenxin Jiang
Some Results on Weakly Accurate Base Learners for Boosting Regression and Classification. Multiple Classifier Systems (2000)
Wenxin Jiang
The VC Dimension for Mixtures of Binary Classifiers. Neural Comput. 12 (6) (2000)
Wenxin Jiang, Martin A. Tanner
On the asymptotic normality of hierarchical mixtures-of-experts for generalized linear models. IEEE Trans. Inf. Theory 46 (3) (2000)
Wenxin Jiang, Martin A. Tanner
Hierarchical mixtures-of-experts for generalized linear models: some results on denseness and consistency. AISTATS (1999)
Wenxin Jiang, Martin A. Tanner
On the Approximation Rate of Hierarchical Mixtures-of-Experts for Generalized Linear Models. Neural Comput. 11 (5) (1999)
Wenxin Jiang, Martin A. Tanner
On the identifiability of mixtures-of-experts. Neural Networks 12 (9) (1999)
Wenxin Jiang, Martin A. Tanner
Hierarchical Mixtures-of-Experts for Exponential Family Regression Models with Generalized Linear Mean Functions: A Survey of Approximation and Consistency Results. UAI (1998)