33 citations · 141 across the 26 of their papers we have counts for
26 papers
Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing
Youwei Shu, Xi Xiao, Derui Wang +5
Randomized Smoothing (RS) is currently a scalable certified defense method providing robustness certification against adversarial examples. Although significant progress has been a…
COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits
Mintong Kang, Nezihe Merve Gürel, Linyi Li +1
Conformal prediction has shown spurring performance in constructing statistically rigorous prediction sets for arbitrary black-box machine learning models, assuming the data is exc…
COMMIT: Certifying Robustness of Multi-Sensor Fusion Systems against Semantic Attacks
Zijian Huang, Wenda Chu, Linyi Li +2
Multi-sensor fusion systems (MSFs) play a vital role as the perception module in modern autonomous vehicles (AVs). Therefore, ensuring their robustness against common and realistic…
Pixel-wise Smoothing for Certified Robustness against Camera Motion Perturbations
Hanjiang Hu, Zuxin Liu, Linyi Li +2
Deep learning-based visual perception models lack robustness when faced with camera motion perturbations in practice. The current certification process for assessing robustness is…
Reliability Assurance for Deep Neural Network Architectures Against Numerical Defects
Linyi Li, Yuhao Zhang, Luyao Ren +2
With the widespread deployment of deep neural networks (DNNs), ensuring the reliability of DNN-based systems is of great importance. Serious reliability issues such as system failu…
Robustness Certification of Visual Perception Models via Camera Motion Smoothing
Hanjiang Hu, Zuxin Liu, Linyi Li +2
A vast literature shows that the learning-based visual perception model is sensitive to adversarial noises, but few works consider the robustness of robotic perception models under…