Publications

Title Venue Links
LieRE: Lie Rotational Positional Encodings
Sophie Ostmeier, Brian Axelrod, Maya Varma, Michael E. Moseley, Akshay Chaudhari, Curtis Langlotz
ICML 2025
Random expert sampling for deep learning segmentation of acute ischemic stroke on non-contrast CT
Sophie Ostmeier, Brian Axelrod, Yilin Liu, Yiming Yu, Bin Jiang, Nancy Yuen, Brian Pulli, et al.
Journal of neurointerventional surgery 2025
On the Statistical Complexity of Sample Amplification
Brian Axelrod, Shivam Garg, Yanjun Han, Vatsal Sharan, Gregory Valiant
Annals of Statistics 2024
Non-inferiority of deep learning ischemic stroke segmentation on non-contrast CT within 16-hours compared to expert neuroradiologists
Sophie Ostmeier, Brian Axelrod, Bram FJ Verhaaren, Stephanie Christensen, Arsany Mahammedi, Akshay Chaudhari, Curtis Langlotz
Scientific Reports 2023
USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging
Sophie Ostmeier, Brian Axelrod, Fabian Isensee, Jeroen Bertels, Maarten Mlynash, Stephanie Christensen, Akshay Chaudhari, Curtis Langlotz
Medical Image Analysis 2023
Sidestepping Hardness in Statistical Problems
Brian Axelrod
PhD Thesis (2022)
Causal Strategic Linear Regression
Yonadav Shavit, Benjamin Edelman, Brian Axelrod
ICML 2020
Near-optimal Approximate Discrete and Continuous Submodular Function Minimization SODA 2020
Sample Amplification: Increasing Dataset Size even when Learning is Impossible ICML 2020
A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families [merged] NeurIPS 2019
An Efficient Algorithm For High-Dimensional Log-Concave Maximum Likelihood [original]
Hardness of 2D Motion Planning Under Obstacle Uncertainty IJRR 2020
Hardness of 3D Motion Planning Under Obstacle Uncertainty WAFR 2018
Provably Safe Robot Navigation with Obstacle Uncertainty (Journal Version) IJRR
Provably Safe Robot Navigation with Obstacle Uncertainty (Conference Version) RSS 2017
Reducing FPGA Algorithm Area by Avoiding Redundant Computation ICRA 2015

Master's Thesis

Brian Axelrod's masters thesis, done under the supervision of Leslie Pack Kaelbling and Tomás Lozano-Pérez at MIT, can be found here.