7 papers
Trust, Don't Trust, or Flip: Robust Preference-Based Reinforcement Learning with Multi-Expert Feedback
Seyed Amir Hosseini, Maryam Abdolali, Amirhosein Tavakkoli +4
Preference-based reinforcement learning (PBRL) offers a promising alternative to explicit reward engineering by learning from pairwise trajectory comparisons. However, real-world p…
Evict3R: Training-Free Token Eviction for Memory-Bounded Streaming Visual Geometry Transformers
Soroush Mahdi, Fardin Ayar, Ehsan Javanmardi +2
Streaming visual transformers like StreamVGGT achieve strong 3D perception but suffer from unbounded growth of key value (KV) memory, which limits scalability. We propose a trainin…
Towards Robust LiDAR Localization: Deep Learning-based Uncertainty Estimation
Minoo Dolatabadi, Fardin Ayar, Ehsan Javanmardi +2
LiDAR-based localization and SLAM often rely on iterative matching algorithms, particularly the Iterative Closest Point (ICP) algorithm, to align sensor data with pre-existing maps…
Adapt, Agree, Aggregate: Semi-Supervised Ensemble Labeling for Graph Convolutional Networks
Maryam Abdolali, Romina Zakerian, Behnam Roshanfekr +2
In this paper, we propose a novel framework that combines ensemble learning with augmented graph structures to improve the performance and robustness of semi-supervised node classi…
Where Do You Go? Pedestrian Trajectory Prediction using Scene Features
Mohammad Ali Rezaei, Fardin Ayar, Ehsan Javanmardi +2
Accurate prediction of pedestrian trajectories is crucial for enhancing the safety of autonomous vehicles and reducing traffic fatalities involving pedestrians. While numerous stud…
Neural Error Covariance Estimation for Precise LiDAR Localization
Minoo Dolatabadi, Fardin Ayar, Ehsan Javanmardi +2
Autonomous vehicles have gained significant attention due to technological advancements and their potential to transform transportation. A critical challenge in this domain is prec…