From Patches to Images: A Nonparametric Generative Model. - Geng Ji 001; Michael C. Hughes; Erik B. Sudderth (ICML, 2017)

Bayesian Paragraph Vectors. - Geng Ji 001; Robert Bamler; Erik B. Sudderth; Stephan Mandt (CoRR, 2017)

Variational Training for Large-Scale Noisy-OR Bayesian Networks. - Geng Ji 001; Dehua Cheng; Huazhong Ning; Changhe Yuan; Hanning Zhou; Liang Xiong; Erik B. Sudderth (UAI, 2019)

Efficient Variational Inference for Hierarchical Models of Images, Text, and Networks. - Geng Ji 001 (2019)

Marginalized Stochastic Natural Gradients for Black-Box Variational Inference. - Geng Ji 001; Debora Sujono; Erik B. Sudderth (ICML, 2021)

MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks. - Yun He 001; Xue Feng; Cheng Cheng; Geng Ji 001; Yunsong Guo; James Caverlee (WWW, 2022)

Correction to: Learning to bid and rank together in recommendation systems. - Geng Ji 001; Wentao Jiang; Jiang Li; Fahmid Morshed Fahid; Zhengxing Chen; Yinghua Li; Jun Xiao; Chongxi Bao; Zheqing Zhu (Mach. Learn., 2024)

Learning to bid and rank together in recommendation systems. - Geng Ji 001; Wentao Jiang; Jiang Li; Fahmid Morshed Fahid; Zhengxing Chen; Yinghua Li; Jun Xiao; Chongxi Bao; Zheqing Zhu (Mach. Learn., 2024)