Brian Axelrod - RankMe

25 papers A* 6C 2Journal 15Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Attention Head Entropy of LLMs Predicts Answer Correctness. CoRR Sophie Ostmeier, Brian Axelrod, Maya Varma, Asad Aali, Yabin Zhang, Magdalini Paschali, Sanmi Koyejo, Curtis Langlotz, Akshay Chaudhari
2025	A*	`conf`	LieRE: Lie Rotational Positional Encodings. ICML Sophie Ostmeier, Brian Axelrod, Maya Varma, Michael E. Moseley, Akshay S. Chaudhari, Curtis Langlotz
2024	J	`jnl`	LieRE: Generalizing Rotary Position Encodings. CoRR Sophie Ostmeier, Brian Axelrod, Michael E. Moseley, Akshay Chaudhari, Curtis P. Langlotz
2023	J	`jnl`	Random Expert Sampling for Deep Learning Segmentation of Acute Ischemic Stroke on Non-contrast CT. CoRR Sophie Ostmeier, Brian Axelrod, Benjamin Pulli, Benjamin F. J. Verhaaren, Abdelkader Mahammedi, Yongkai Liu, Christian Federau, Greg Zaharchuk, Jeremy J. Heit
2023	J	`jnl`	USE-Evaluator: Performance metrics for medical image segmentation models supervised by uncertain, small or empty reference annotations in neuroimaging. Medical Image Anal. Sophie Ostmeier, Brian Axelrod, Fabian Isensee, Jeroen Bertels, Michael Mlynash, Soren Christensen, Maarten G. Lansberg, Gregory W. Albers, Rajen Sheth, Benjamin F. J. Verhaaren, Abdelkader Mahammedi, Li-Jia Li, Greg Zaharchuk, Jeremy J. Heit
2022	C	`conf`	Efficient Motion Planning Under Obstacle Uncertainty with Local Dependencies. WAFR Brian Axelrod, Luke Shimanuki
2022	J	`jnl`	Evaluation of Medical Image Segmentation Models for Uncertain, Small or Empty Reference Annotations. CoRR Sophie Ostmeier, Brian Axelrod, Jeroen Bertels, Fabian Isensee, Maarten G. Lansberg, Soren Christensen, Gregory W. Albers, Li-Jia Li, Jeremy J. Heit
2022	J	`jnl`	Non-inferiority of Deep Learning Model to Segment Acute Stroke on Non-contrast CT Compared to Neuroradiologists. CoRR Sophie Ostmeier, Jeremy J. Heit, Brian Axelrod, Li-Jia Li, Greg Zaharchuk, Benjamin F. J. Verhaaren, Abdelkader Mahammedi, Soren Christensen, Maarten G. Lansberg
2022	J	`jnl`	On the Statistical Complexity of Sample Amplification. CoRR Brian Axelrod, Shivam Garg, Yanjun Han, Vatsal Sharan, Gregory Valiant
2022	—	`—`	Sidestepping hardness in statistical problems. Brian Axelrod
2021	J	`jnl`	Hardness of Motion Planning with Obstacle Uncertainty in Two Dimensions. Int. J. Robotics Res. Luke Shimanuki, Brian Axelrod
2020	A*	`conf`	Causal Strategic Linear Regression. ICML Yonadav Shavit, Benjamin L. Edelman, Brian Axelrod
2020	J	`jnl`	Learning From Strategic Agents: Accuracy, Improvement, and Causality. CoRR Yonadav Shavit, Benjamin L. Edelman, Brian Axelrod
2020	A*	`conf`	Near-optimal Approximate Discrete and Continuous Submodular Function Minimization. SODA Brian Axelrod, Yang P. Liu, Aaron Sidford
2020	A*	`conf`	Sample Amplification: Increasing Dataset Size even when Learning is Impossible. ICML Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant
2019	A*	`conf`	A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families. NeurIPS Brian Axelrod, Ilias Diakonikolas, Alistair Stewart, Anastasios Sidiropoulos, Gregory Valiant
2019	J	`jnl`	A Polynomial Time Algorithm for Log-Concave Maximum Likelihood via Locally Exponential Families. CoRR Brian Axelrod, Ilias Diakonikolas, Anastasios Sidiropoulos, Alistair Stewart, Gregory Valiant
2019	J	`jnl`	Near-optimal Approximate Discrete and Continuous Submodular Function Minimization. CoRR Brian Axelrod, Yang P. Liu, Aaron Sidford
2019	J	`jnl`	Sample Amplification: Increasing Dataset Size even when Learning is Impossible. CoRR Brian Axelrod, Shivam Garg, Vatsal Sharan, Gregory Valiant
2018	J	`jnl`	An Efficient Algorithm for High-Dimensional Log-Concave Maximum Likelihood. CoRR Brian Axelrod, Gregory Valiant
2018	C	`conf`	Hardness of 3D Motion Planning Under Obstacle Uncertainty. WAFR Luke Shimanuki, Brian Axelrod
2018	J	`jnl`	Provably safe robot navigation with obstacle uncertainty. Int. J. Robotics Res. Brian Axelrod, Leslie Pack Kaelbling, Tomás Lozano-Pérez
2017	—	`conf`	Provably Safe Robot Navigation with Obstacle Uncertainty. Robotics: Science and Systems Brian Axelrod, Leslie Pack Kaelbling, Tomás Lozano-Pérez
2017	J	`jnl`	Provably Safe Robot Navigation with Obstacle Uncertainty. CoRR Brian Axelrod, Leslie Pack Kaelbling, Tomás Lozano-Pérez
2015	A*	`conf`	Reducing FPGA algorithm area by avoiding redundant computation. ICRA Brian Axelrod, Michel Laverne