Joint estimation of gene conversion rates and mean conversion tract lengths from population SNP data. - Junming Yin; Michael I. Jordan; Yun S. Song (Bioinform., 2009)

Computational Methods for Meiotic Recombination Inference. - Junming Yin (2010)

Group Sparse Additive Models. - Junming Yin; Xi Chen 010; Eric P. Xing (ICML, 2012)

On Triangular versus Edge Representations — Towards Scalable Modeling of Networks. - Qirong Ho; Junming Yin; Eric P. Xing (NIPS, 2012)

Finding Genome-Transcriptome-Phenome Associations with Structured Association Mapping and Visualization in GenAMap. - Ross E. Curtis; Junming Yin; Peter Kinnaird; Eric P. Xing (Pacific Symposium on Biocomputing, 2012)

A Scalable Approach to Probabilistic Latent Space Inference of Large-Scale Networks. - Junming Yin; Qirong Ho; Eric P. Xing (NIPS, 2013)

Petuum: A Framework for Iterative-Convergent Distributed ML. - Wei Dai 003; Jinliang Wei; Xun Zheng; Jin Kyu Kim; Seunghak Lee; Junming Yin; Qirong Ho; Eric P. Xing (CoRR, 2013)

Identifying High Quality Carding Services in Underground Economy using Nonparametric Supervised Topic Model. - Weifeng Li 002; Junming Yin; Hsinchun Chen (ICIS, 2016)

Targeting key data breach services in underground supply chain. - Weifeng Li 002; Junming Yin; Hsinchun Chen (ISI, 2016)

A time-varying group sparse additive model for genome-wide association studies of dynamic complex traits. - Micol Marchetti-Bowick; Junming Yin; Judie A. Howrylak; Eric P. Xing (Bioinform., 2016)

Latent Space Inference of Internet-Scale Networks. - Qirong Ho; Junming Yin; Eric P. Xing (J. Mach. Learn. Res., 2016)

Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks. - Linhong Zhu; Dong Guo; Junming Yin; Greg Ver Steeg; Aram Galstyan (IEEE Trans. Knowl. Data Eng., 2016)

Scalable Temporal Latent Space Inference for Link Prediction in Dynamic Social Networks (Extended Abstract). - Linhong Zhu; Dong Guo; Junming Yin; Greg Ver Steeg; Aram Galstyan (ICDE, 2017)

Convex-constrained Sparse Additive Modeling and Its Extensions. - Junming Yin; Yaoliang Yu (UAI, 2017)

Supervised Topic Modeling Using Hierarchical Dirichlet Process-Based Inverse Regression: Experiments on E-Commerce Applications. - Weifeng Li 002; Junming Yin; Hsinchun Chen (IEEE Trans. Knowl. Data Eng., 2018)

Deep Reinforcement Learning for Personalized Search Story Recommendation. - Jason Zhang; Junming Yin; Dongwon Lee 001; Linhong Zhu (CoRR, 2019)

Relaxed Multivariate Bernoulli Distribution and Its Applications to Deep Generative Models. - Xi Wang; Junming Yin (UAI, 2020)

Learning from Crowdsourced Multi-labeling: A Variational Bayesian Approach. - Junming Yin; Jerry Luo; Susan A. Brown (Inf. Syst. Res., 2021)

Bandit Learning in Many-to-One Matching Markets. - Zilong Wang 010; Liya Guo; Junming Yin; Shuai Li 010 (CIKM, 2022)

Thompson Sampling for Bandit Learning in Matching Markets. - Fang Kong 002; Junming Yin; Shuai Li 010 (IJCAI, 2022)

Bridging Music and Text with Crowdsourced Music Comments: A Sequence-to-Sequence Framework for Thematic Music Comments Generation. - Peining Zhang; Junliang Guo; Linli Xu; Mu You; Junming Yin (CoRR, 2022)

Modeling Behavioral Dynamics in Digital Content Consumption: An Attention-Based Neural Point Process Approach with Applications in Video Games. - Junming Yin; Yue (Katherine) Feng; Yong Liu (Mark. Sci., 2025)