Results 91 to 100 of about 2,268,403 (339)

scPER: A Rigorous Computational Approach to Determine Cellular Subtypes in Tumors Aligned With Cancer Phenotypes From Total RNA Sequencing

open access: yesAdvanced Science, EarlyView.
scPER presents an adversarial‐autoencoder framework that deconvolves bulk total RNA‐seq to quantify tumor‐microenvironment cell types and uncover phenotype‐linked subclusters. Across diverse benchmarks, scPER improves accuracy over existing tools.
Bingrui Li, Xiaobo Zhou, Raghu Kalluri
wiley   +1 more source

A knowledge distillation strategy for enhancing the adversarial robustness of lightweight automatic modulation classification models

open access: yesIET Communications
Automatic modulation classification models based on deep learning models are at risk of being interfered by adversarial attacks. In an adversarial attack, the attacker causes the classification model to misclassify the received signal by adding carefully
Fanghao Xu   +5 more
doaj   +1 more source

Solid Harmonic Wavelet Bispectrum for Image Analysis

open access: yesAdvanced Science, EarlyView.
The Solid Harmonic Wavelet Bispectrum (SHWB), a rotation‐ and translation‐invariant descriptor that captures higher‐order (phase) correlations in signals, is introduced. Combining wavelet scattering, bispectral analysis, and group theory, SHWB achieves interpretable, data‐efficient representations and demonstrates competitive performance across texture,
Alex Brown   +3 more
wiley   +1 more source

Nanozymes Integrated Biochips Toward Smart Detection System

open access: yesAdvanced Science, EarlyView.
This review systematically outlines the integration of nanozymes, biochips, and artificial intelligence (AI) for intelligent biosensing. It details how their convergence enhances signal amplification, enables portable detection, and improves data interpretation.
Dongyu Chen   +10 more
wiley   +1 more source

Knowing is Half the Battle: Enhancing Clean Data Accuracy of Adversarial Robust Deep Neural Networks via Dual-Model Bounded Divergence Gating

open access: yesIEEE Access
Significant advances have been made in recent years in improving the robustness of deep neural networks, particularly under adversarial machine learning scenarios where the data has been contaminated to fool networks into making undesirable predictions ...
Hossein Aboutalebi   +3 more
doaj   +1 more source

A Formalization of Robustness for Deep Neural Networks

open access: yes, 2019
Deep neural networks have been shown to lack robustness to small input perturbations. The process of generating the perturbations that expose the lack of robustness of neural networks is known as adversarial input generation.
Dreossi, Tommaso   +3 more
core  

Robust Universal Adversarial Perturbations

open access: yes, 2022
16 pages, 3 ...
Xu, Changming, Singh, Gagandeep
openaire   +2 more sources

Reconstructing Coherent Functional Landscape From Multi‐Modal Multi‐Slice Spatial Transcriptomics by a Variational Spatial Gaussian Process

open access: yesAdvanced Science, EarlyView.
This study introduces stVGP, a variational spatial Gaussian process framework for multi‐modal, multi‐slice spatial transcriptomics. By integrating histological and genomic data through hybrid alignment and attention‐based fusion, stVGP reconstructs coherent 3D functional landscapes.
Zedong Wang   +3 more
wiley   +1 more source

Improving model adversarial robustness in Extractive Question Answering via Wasserstein-Guided feature Representations

open access: yesAlexandria Engineering Journal
Extractive Question Answering (EQA) models aim to locate accurate answers from passages given a question but are highly susceptible to adversarial attacks.
Gang Huang, Lu Zhang, Hailun Wang
doaj   +1 more source

A Unified Game-Theoretic Interpretation of Adversarial Robustness [PDF]

open access: green, 2021
Ren, Jie   +10 more
openalex   +1 more source

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