10 citations · 21 across the 8 of their papers we have counts for
8 papers
PQV-Mobile: A Combined Pruning and Quantization Toolkit to Optimize Vision Transformers for Mobile Applications
Kshitij Bhardwaj
While Vision Transformers (ViTs) are extremely effective at computer vision tasks and are replacing convolutional neural networks as the new state-of-the-art, they are complex and…
Scaling Compute Is Not All You Need for Adversarial Robustness
Edoardo Debenedetti, Zishen Wan, Maksym Andriushchenko +3
The last six years have witnessed significant progress in adversarially robust deep learning. As evidenced by the CIFAR-10 dataset category in RobustBench benchmark, the accuracy u…
Machine Learning-Enhanced Prediction of Surface Smoothness for Inertial Confinement Fusion Target Polishing Using Limited Data
Antonios Alexos, Junze Liu, Akash Tiwari +5
In Inertial Confinement Fusion (ICF) process, roughly a 2mm spherical shell made of high density carbon is used as target for laser beams, which compress and heat it to energy leve…
Real-Time Fully Unsupervised Domain Adaptation for Lane Detection in Autonomous Driving
Kshitij Bhardwaj, Zishen Wan, Arijit Raychowdhury +1
While deep neural networks are being utilized heavily for autonomous driving, they need to be adapted to new unseen environmental conditions for which they were not trained. We foc…
Benchmarking Test-Time Unsupervised Deep Neural Network Adaptation on Edge Devices
Kshitij Bhardwaj, James Diffenderfer, Bhavya Kailkhura +1
The prediction accuracy of the deep neural networks (DNNs) after deployment at the edge can suffer with time due to shifts in the distribution of the new data. To improve robustnes…
Roofline Model for UAVs:A Bottleneck Analysis Tool for Designing Compute Systems for Autonomous Drones
Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj +2
We present a bottleneck analysis tool for designing compute systems for autonomous Unmanned Aerial Vehicles (UAV). The tool provides insights by exploiting the fundamental relation…
Semi-supervised on-device neural network adaptation for remote and portable laser-induced breakdown spectroscopy
Kshitij Bhardwaj, Maya Gokhale
Laser-induced breakdown spectroscopy (LIBS) is a popular, fast elemental analysis technique used to determine the chemical composition of target samples, such as in industrial anal…
SMAUG: End-to-End Full-Stack Simulation Infrastructure for Deep Learning Workloads
Sam Likun Xi, Yuan Yao, Kshitij Bhardwaj +3
In recent years, there has been tremendous advances in hardware acceleration of deep neural networks. However, most of the research has focused on optimizing accelerator microarchi…