Bayesian learning of joint distributions of objects. - Anjishnu Banerjee; Jared Murray; David B. Dunson (AISTATS, 2013)

Classification before Segmentation: Improved U-Net Prostate Segmentation. - Ronald J. Nowling; John Bukowy; Sean D. McGarry; Andrew S. Nencka; Oliver Blasko; Jay Urbain; Allison K. Lowman; Alexander Barrington; Anjishnu Banerjee; Kenneth A. Iczkowski; Peter S. LaViolette (BHI, 2019)

Co-registration tool for large format whole mount prostate multi-plex histology. - Michael Brehler; Allison K. Lowman; Samuel Bobholz; Sean D. McGarry; Anjishnu Banerjee; Kenneth A. Iczkowski; Peter S. LaViolette (Digital Pathology, 2021)

Personalized Federated Learning for Gastric Cancer: Adaptive Inference from Large Heterogeneous Piecewise Electronic Health Record Based Biomedical Data. - Hengrui Hu; Anai N. Kothari; Anjishnu Banerjee (IEEE Big Data, 2024)

Stronger Baseline Models - A Key Requirement for Aligning Machine Learning Research with Clinical Utility. - Nathan Wolfrath; Joel Wolfrath; Hengrui Hu; Anjishnu Banerjee; Anai N. Kothari (CoRR, 2024)

A Novel Algorithm for Personalized Federated Learning: Knowledge Distillation with Weighted Combination Loss. - Hengrui Hu; Anai N. Kothari; Anjishnu Banerjee (CoRR, 2025)