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ResearchTrend.AI
Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs

Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs

Lorena Qendro
Sangwon Ha
R. D. Jong
Partha P. Maji
ArXiv (abs)PDFHTML

Papers citing "Stochastic-Shield: A Probabilistic Approach Towards Training-Free Adversarial Defense in Quantized CNNs"

2 / 2 papers shown
Title
ARQ: A Mixed-Precision Quantization Framework for Accurate and Certifiably Robust DNNs
ARQ: A Mixed-Precision Quantization Framework for Accurate and Certifiably Robust DNNs
Yuchen Yang
Shubham Ugare
Yifan Zhao
Gagandeep Singh
Sasa Misailovic
MQ
151
0
0
31 Oct 2024
When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA
When Monte-Carlo Dropout Meets Multi-Exit: Optimizing Bayesian Neural Networks on FPGA
Hongxiang Fan
Hao Mark Chen
Liam Castelli
Zhiqiang Que
He Li
Kenneth Long
Wayne Luk
BDL
59
2
0
13 Aug 2023

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