2 citations · 3 across the 7 of their papers we have counts for
7 papers
TOOD: Task-Aware Out-of-Distribution Score Calibration for Continual Learners
Mostafa ElAraby, Samer B. Nashed, Liam Paull
The primary challenge of continual learning (CL) systems is to learn new tasks while remaining performant on previously learned tasks. A similarly important though less well-studie…
Perpetua: Multi-Hypothesis Persistence Modeling for Semi-Static Environments
Miguel Saavedra-Ruiz, Samer B. Nashed, Charlie Gauthier +1
Many robotic systems require extended deployments in complex, dynamic environments. In such deployments, parts of the environment may change between subsequent robot observations.…
Safety Representations for Safer Policy Learning
Kaustubh Mani, Vincent Mai, Charlie Gauthier +3
Reinforcement learning algorithms typically necessitate extensive exploration of the state space to find optimal policies. However, in safety-critical applications, the risks assoc…
The Harmonic Exponential Filter for Nonparametric Estimation on Motion Groups
Miguel Saavedra-Ruiz, Steven A. Parkison, Ria Arora +2
Bayesian estimation is a vital tool in robotics as it allows systems to update the robot state belief using incomplete information from noisy sensors. To render the state estimatio…
BACS: Background Aware Continual Semantic Segmentation
Mostafa ElAraby, Ali Harakeh, Liam Paull
Semantic segmentation plays a crucial role in enabling comprehensive scene understanding for robotic systems. However, generating annotations is challenging, requiring labels for e…
GROOD: GRadient-Aware Out-of-Distribution Detection
Mostafa ElAraby, Sabyasachi Sahoo, Yann Pequignot +2
Out-of-distribution (OOD) detection is crucial for ensuring the reliability of deep learning models in real-world applications. Existing methods typically focus on feature represen…
Ghost on the Shell: An Expressive Representation of General 3D Shapes
Zhen Liu, Yao Feng, Yuliang Xiu +4
The creation of photorealistic virtual worlds requires the accurate modeling of 3D surface geometry for a wide range of objects. For this, meshes are appealing since they 1) enable…