3 papers
cs.LG2025
NeuroSep-CP-LCB: A Deep Learning-based Contextual Multi-armed Bandit Algorithm with Uncertainty Quantification for Early Sepsis Prediction
Anni Zhou, Raheem Beyah, Rishikesan Kamaleswaran
In critical care settings, timely and accurate predictions can significantly impact patient outcomes, especially for conditions like sepsis, where early intervention is crucial. We…
cs.LG2025
Sepsyn-OLCP: An Online Learning-based Framework for Early Sepsis Prediction with Uncertainty Quantification using Conformal Prediction
Anni Zhou, Beyah Raheem, Rishikesan Kamaleswaran +1
Sepsis is a life-threatening syndrome with high morbidity and mortality in hospitals. Early prediction of sepsis plays a crucial role in facilitating early interventions for septic…
cs.NI2024
Synergistic Interplay of Large Language Model and Digital Twin for Autonomous Optical Networks: Field Demonstrations
Yuchen Song, Yao Zhang, Anni Zhou +6
The development of large language models (LLM) has revolutionized various fields and is anticipated to drive the advancement of autonomous systems. In the context of autonomous opt…