83 citations · 94 across the 18 of their papers we have counts for
7 papers · 1 filter
Conformalized Multimodal Uncertainty Regression and Reasoning
Domenico Parente, Nastaran Darabi, Alex C. Stutts +2
This paper introduces a lightweight uncertainty estimator capable of predicting multimodal (disjoint) uncertainty bounds by integrating conformal prediction with a deep-learning re…
Mutual Information-calibrated Conformal Feature Fusion for Uncertainty-Aware Multimodal 3D Object Detection at the Edge
Alex C. Stutts, Danilo Erricolo, Sathya Ravi +2
In the expanding landscape of AI-enabled robotics, robust quantification of predictive uncertainties is of great importance. Three-dimensional (3D) object detection, a critical rob…
ADC/DAC-Free Analog Acceleration of Deep Neural Networks with Frequency Transformation
Nastaran Darabi, Maeesha Binte Hashem, Hongyi Pan +3
The edge processing of deep neural networks (DNNs) is becoming increasingly important due to its ability to extract valuable information directly at the data source to minimize lat…
Towards Model-Size Agnostic, Compute-Free, Memorization-based Inference of Deep Learning
Davide Giacomini, Maeesha Binte Hashem, Jeremiah Suarez +2
The rapid advancement of deep neural networks has significantly improved various tasks, such as image and speech recognition. However, as the complexity of these models increases,…
Memory-Immersed Collaborative Digitization for Area-Efficient Compute-in-Memory Deep Learning
Shamma Nasrin, Maeesha Binte Hashem, Nastaran Darabi +4
This work discusses memory-immersed collaborative digitization among compute-in-memory (CiM) arrays to minimize the area overheads of a conventional analog-to-digital converter (AD…
Lightweight, Uncertainty-Aware Conformalized Visual Odometry
Alex C. Stutts, Danilo Erricolo, Theja Tulabandhula +1
Data-driven visual odometry (VO) is a critical subroutine for autonomous edge robotics, and recent progress in the field has produced highly accurate point predictions in complex e…
Roadmap for Unconventional Computing with Nanotechnology
Giovanni Finocchio, Jean Anne C. Incorvia, Joseph S. Friedman +48
In the "Beyond Moore's Law" era, with increasing edge intelligence, domain-specific computing embracing unconventional approaches will become increasingly prevalent. At the same ti…