Dynamic Neural Network is All You Need: Understanding the Robustness of Dynamic Mechanisms in Neural Networks

17 August 2023

Papers citing "Dynamic Neural Network is All You Need: Understanding the Robustness of Dynamic Mechanisms in Neural Networks"

5 / 5 papers shown

Title
The Impact of Uniform Inputs on Activation Sparsity and Energy-Latency Attacks in Computer Vision Andreas Müller Erwin Quiring AAML 34 1 0 27 Mar 2024
DeepPerform: An Efficient Approach for Performance Testing of Resource-Constrained Neural Networks Simin Chen Mirazul Haque Cong Liu Wei Yang 45 21 0 10 Oct 2022
LLMEffiChecker: Understanding and Testing Efficiency Degradation of Large Language Models Simin Chen Cong Liu Mirazul Haque Wei Yang 34 21 0 07 Oct 2022
Learning to Reverse DNNs from AI Programs Automatically Simin Chen Hamed Khanpour Cong Liu Wei Yang 35 15 0 20 May 2022
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications Andrew G. Howard Menglong Zhu Bo Chen Dmitry Kalenichenko Weijun Wang Tobias Weyand M. Andreetto Hartwig Adam 3DH 950 20,567 0 17 Apr 2017