Multi-task Learning of Order-Consistent Causal Graphs. - Xinshi Chen; Haoran Sun; Caleb Ellington; Eric P. Xing; Le Song (NeurIPS, 2021)

NOTMAD: Estimating Bayesian Networks with Sample-Specific Structures and Parameters. - Benjamin J. Lengerich; Caleb Ellington; Bryon Aragam; Eric P. Xing; Manolis Kellis (CoRR, 2021)

Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case study. - Benjamin J. Lengerich; Mark E. Nunnally; Yin Aphinyanaphongs; Caleb Ellington; Rich Caruana (J. Biomed. Informatics, 2022)

Machine Learning for Health (ML4H) 2023. - Stefan Hegselmann; Antonio Parziale; Divya Shanmugam; Shengpu Tang; Kristen Severson 001; Mercy Nyamewaa Asiedu; Serina Chang; Bonaventure F. P. Dossou; Qian Huang; Fahad Kamran; Haoran Zhang 003; Sujay Nagaraj; et al. (ML4H@NeurIPS, 2023)

Contextualized Machine Learning. - Benjamin J. Lengerich; Caleb N. Ellington; Andrea Rubbi; Manolis Kellis; Eric P. Xing (CoRR, 2023)

Contextualized Policy Recovery: Modeling and Interpreting Medical Decisions with Adaptive Imitation Learning. - Jannik Deuschel; Caleb Ellington; Yingtao Luo; Benjamin J. Lengerich; Pascal Friederich; Eric P. Xing (ICML, 2024)

Machine Learning for Health (ML4H) 2024. - Helen Zhou; Stefan Hegselmann; Elizabeth Healey; Trenton Chang; Caleb Ellington; Michael Leone; Vishwali Mhasawade; Sana Tonekaboni; Winston Chen; Hyewon Jeong; Xiaoxiao Li; Juyeon Heo; et al. (ML4H@NeurIPS, 2024)

AttentionPert: accurately modeling multiplexed genetic perturbations with multi-scale effects. - Ding Bai; Caleb N. Ellington; Shentong Mo; Le Song; Eric P. Xing (Bioinform., 2024)

Patient-Specific Models of Treatment Effects Explain Heterogeneity in Tuberculosis. - Ethan Wu; Caleb Ellington; Benjamin J. Lengerich; Eric P. Xing (CoRR, 2024)

SPRINT Enables Interpretable and Ultra-Fast Virtual Screening against Thousands of Proteomes. - Andrew T. McNutt; Abhinav Adduri; Caleb N. Ellington; Monica T. Dayao; Eric P. Xing; Hosein Mohimani; David Ryan Koes (CoRR, 2024)

Contextualized: Heterogeneous Modeling Toolbox. - Caleb N. Ellington; Benjamin J. Lengerich; Wesley Lo; Aaron Alvarez; Andrea Rubbi; Manolis Kellis; Eric P. Xing (J. Open Source Softw., 2024)

Machine Learning for Health symposium 2024 - Findings track. - Stefan Hegselmann; Helen Zhou; Elizabeth Healey; Trenton Chang; Caleb Ellington; Vishwali Mhasawade; Sana Tonekaboni; Peniel N. Argaw; Haoran Zhang 003 (CoRR, 2025)