79 citations · 81 across the 2 of their papers we have counts for
2 papers
stat.CO2023★ 2 cited
Efficiently analyzing large patient registries with Bayesian joint models for longitudinal and time-to-event data
P. Miranda Afonso, D. Rizopoulos, A. K. Palipana +4
The joint modeling of longitudinal and time-to-event outcomes has become a popular tool in follow-up studies. However, fitting Bayesian joint models to large datasets, such as pati…
cs.IR2023★ 79 cited
Multi-behavior Self-supervised Learning for Recommendation
Jingcao Xu, Chaokun Wang, Cheng Wu +6
Modern recommender systems often deal with a variety of user interactions, e.g., click, forward, purchase, etc., which requires the underlying recommender engines to fully understa…