Student at the University of Alberta, who is lucky to be supervised by Dr. Csaba Szepesvári. Current research is focused on the theory of algorithms for sequential decision making problems, and in particular getting fast rates.
[0] Switching the Loss Reduces the Cost in Batch Reinforcement Learning
[ICML 2024] Alex Ayoub, Kaiwen Wang, Vincent Liu, Samuel Robertson, James McInerney, Dawen Liang, Nathan Kallus, Csaba Szepesvári
[1] Stroke lesion localization in 3D MRI datasets with deep reinforcement learning
[SPIE Medical Imaging 2022: Computer-Aided Diagnosis] by Samuel Robertson, Anup Tuladhar, Deepthi Rajashekar, Nils D Forkert
[2] Quantifying the relationship between cell proliferation and morphology during development of the face
[Preprint] by Rebecca M Green, Lucas D Lo Vercio, Andreas Dauter, Elizabeth C Barretto, Jay Devine, Marta Vidal-García, Marta Marchini, Samuel Robertson, Xiang Zhao, Anandita Mahika, M Bilal Shakir, Sienna Guo, Julia C Boughner, Wendy Dean, Arthur D Lander, Ralph S Marcucio, Nils D Forkert, Benedikt Hallgrímsson
[3] Segmentation of Tissues and Proliferating Cells in Light-Sheet Microscopy Images of Mouse Embryos using Convolutional Neural Networks
[IEEE Access 2022/9/28] by Lucas D Lo Vercio, Rebecca M Green, Samuel Robertson, Sienna Guo, Andreas Dauter, Marta Marchini, Marta Vidal-García, Xiang Zhao, Anandita Mahika, Ralph S Marcucio, Benedikt Hallgrímsson, Nils D Forkert