4 citations · 9 across the 31 of their papers we have counts for
5 papers · 1 filter
Neural Precision Polarization: Simplifying Neural Network Inference with Dual-Level Precision
Dinithi Jayasuriya, Nastaran Darabi, Maeesha Binte Hashem +1
We introduce a precision polarization scheme for DNN inference that utilizes only very low and very high precision levels, assigning low precision to the majority of network weight…
Enhancing 3D Robotic Vision Robustness by Minimizing Adversarial Mutual Information through a Curriculum Training Approach
Nastaran Darabi, Dinithi Jayasuriya, Devashri Naik +2
Adversarial attacks exploit vulnerabilities in a model's decision boundaries through small, carefully crafted perturbations that lead to significant mispredictions. In 3D vision, t…
Sense Less, Generate More: Pre-training LiDAR Perception with Masked Autoencoders for Ultra-Efficient 3D Sensing
Sina Tayebati, Theja Tulabandhula, Amit R. Trivedi
In this work, we propose a disruptively frugal LiDAR perception dataflow that generates rather than senses parts of the environment that are either predictable based on the extensi…
Echoes of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement Learning
Alex Christopher Stutts, Danilo Erricolo, Theja Tulabandhula +1
We present a novel statistical approach to incorporating uncertainty awareness in model-free distributional reinforcement learning involving quantile regression-based deep Q networ…
Navigating the Unknown: Uncertainty-Aware Compute-in-Memory Autonomy of Edge Robotics
Nastaran Darabi, Priyesh Shukla, Dinithi Jayasuriya +3
This paper addresses the challenging problem of energy-efficient and uncertainty-aware pose estimation in insect-scale drones, which is crucial for tasks such as surveillance in co…