3 papers
cs.LG2026
Interaction-Limited Safe Continuous-Time RL for Dynamical Medical Treatment
Xun Shen, Yuepeng Wang, Akifumi Wachi +13
Dynamic medical treatment requires deciding treatment intensity and intervention timing, while patient states evolve continuously and adverse events may occur between clinical inte…
cs.LG2026
MedGym:A Unified Continuous-Time Benchmark for Dynamic Medical Treatment Reinforcement Learning
Yuepeng Wang, Ken Kawano, Yongqi Zhou +11
Medical treatment recommendation poses several challenges to reinforcement learning (RL): patient physiology evolves in continuous time, measurements and interventions are performe…
cs.LG2026
PRiMeFlow: Capturing Complex Expression Heterogeneity in Perturbation Response Modelling
Zichao Yan, Yan Wu, Mica Xu Ji +10
Predicting the effects of perturbations in-silico on cell state can identify drivers of cell behavior at scale and accelerate drug discovery. However, modeling challenges remain du…