Results 61 to 70 of about 1,662,189 (295)
When adversarial examples are excusable
CoRR, 2022 Neural networks work remarkably well in practice and theoretically they can be universal approximators. However, they still make mistakes and a specific type of them called adversarial errors seem inexcusable to humans. In this work, we analyze both test errors and adversarial errors on a well controlled but highly non-linear visual classification ...
Pieter-Jan Kindermans, Charles Staats
openaire +2 more sources
Improving Adversarial Robustness of CNNs via Maximum Margin
Applied Sciences, 2022 In recent years, adversarial examples have aroused widespread research interest and raised concerns about the safety of CNNs. We study adversarial machine learning inspired by a support vector machine (SVM), where the decision boundary with maximum ...
Jiaping Wu, Zhaoqiang Xia, Xiaoyi Feng
doaj +1 more source
Advanced Functional Materials, EarlyView.A systematic review is conducted to assess the influence of electrode architecture across micro‐ to mesoscopic length scales on electron‐transfer pathways in electrocatalysis. We discuss the structure‐activity relationships in electrocatalytic applications, including resource recovery and environmental remediation, and provide cost‐effective, efficient
Manshu Zhao +6 more
wiley +1 more source
Adversarial Examples Are Not Bugs, They Are Features
CoRR, 2019 Adversarial examples have attracted significant attention in machine learning, but the reasons for their existence and pervasiveness remain unclear. We demonstrate that adversarial examples can be directly attributed to the presence of non-robust features: features derived from patterns in the data distribution that are highly predictive, yet brittle ...
Ilyas, A +5 more
openaire +4 more sources
Role of Structural Disorder on Phonon Transport and Thermal Conductivity in Li6PS5Br
Advanced Functional Materials, EarlyView.Solid electrolytes are fast ion and slow heat conductors. Although both transport properties are governed by lattice dynamics and atomic structure, their interplay remains poorly understood. Here, we study this interrelation in anion‐ordered and disordered Li6PS5Br.
Lukas Ketter +4 more
wiley +1 more source
Maxwell’s Demon in MLP-Mixer: towards transferable adversarial attacks
CybersecurityModels based on MLP-Mixer architecture are becoming popular, but they still suffer from adversarial examples. Although it has been shown that MLP-Mixer is more robust to adversarial attacks compared to convolutional neural networks (CNNs), there has been
Haoran Lyu +5 more
doaj +1 more source
Advanced Materials, EarlyView.This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
wiley +1 more source
Advanced Materials, EarlyView.Self‐invalidating multilayer physical unclonable functions (PUFs) integrate fingerprint‐like metal nanopattern bilayers from block copolymer templates with highly reactive reduced graphene oxide (rGO) interlayers. This tamper‐responsive architecture blocks all unauthorized physical and chemical replication attempts while autonomously deactivating ...
Gyu Hui Jo +7 more
wiley +1 more source
Enhancing Machine Learning Security: The Significance of Realistic Adversarial Examples [PDF]
Adversarial attacks pose a significant security threat in Machine Learning (ML), employing subtle, invisible perturbations on original examples to craft instances that deceive model decisions.
DYRMISHI, Salijona
core +1 more source
Ensemble Adversarial Example Defense Based on Generative Adversarial Network
工程科学与技术, 2022 Given the bottlenecks of existing adversarial example defense schemes, such as insufficient defense capability and high time consumption, an ensemble adversarial example defense scheme based on the generative adversarial network was proposed in this ...
Tianjie CAO +5 more
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