2 papers
cs.LG2025
ICR-RL: Deep Reinforcement Learning via In-Context Regression
David Schiff, Ofir Lindenbaum, Yonathan Efroni
Recent advancements in machine learning have largely been driven by foundation models (FMs) trained on large, diverse datasets, enabling them to generalize effectively to new, rela…
eess.IV2024
An end-to-end deep learning pipeline to derive blood input with partial volume corrections for automated parametric brain PET mapping
Rugved Chavan, Gabriel Hyman, Zoraiz Qureshi +10
Dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (dFDG-PET) for human brain imaging has considerable clinical potential, yet its utilization remains limited. A…