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Mohammed Elmahgiubi

4 accepted papers

2026

CAPS: Context-Aware Priority Sampling for Enhanced Imitation Learning in Autonomous Driving

Hamidreza Mirkhani, Behzad Khamidehi, Ehsan Ahmadi, Mohammed Elmahgiubi, Weize Zhang, Fazel Arasteh +3
ICRA 2026poster

In this paper, we introduce Context-Aware Priority Sampling (CAPS), a novel method designed to enhance data efficiency in learning-based autonomous driving systems. CAPS addresses the challenge of imbalanced datasets in imitation learning by leveraging Vector Quantized Variational Autoencoders (VQ-V…

Cited by 0Source ↗PDF ↗Scholar ↗
2025

Beyond Simulation: Benchmarking World Models for Planning and Causality in Autonomous Driving

Hunter Schofield, Mohammed Elmahgiubi, Kasra Rezaee, Jinjun Shan
ICRA 2025

World models have become increasingly popular in acting as learned traffic simulators. Recent work has explored replacing traditional traffic simulators with world models for policy training. In this work, we explore the robustness of existing metrics to evaluate world models as traffic simulators t

Cited by 1Source ↗Scholar ↗
2025

Validity Learning on Failures: Mitigating the Distribution Shift in Autonomous Vehicle Planning

Fazel Arasteh, Mohammed Elmahgiubi, Behzad Khamidehi, Hamidreza Mirkhani, Weize Zhang, Tongtong Cao +1
ICRA 2025

The planning problem constitutes a fundamental aspect of the autonomous driving framework. Recent strides in representation learning have empowered vehicles to comprehend their surrounding environments, thereby facilitating the integration of learning-based planning strategies. Among these approache

Cited by 7Source ↗Scholar ↗
2024

Confidence Aware Inverse Constrained Reinforcement Learning

Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi, Kasra Rezaee, Pascal Poupart
ICML 2024poster

In coming up with solutions to real-world problems, humans implicitly adhere to constraints that are too numerous and complex to be specified completely. However, reinforcement learning (RL) agents need these constraints to learn the correct optimal policy in these settings. The field of Inverse Con…

Cited by 6Source ↗PDF ↗code ↗Scholar ↗