Results 61 to 70 of about 234,412 (208)
Med Research, EarlyView.This review details a three‐stage paradigm shift for tumor‐reactive CD8+ T‐cell identification: decoding transcriptomic states, deciphering clonal functional efficacy, and molecular‐level therapeutic TCR design. Addressing translational hurdles and generative AI “scientific blind spots”—such as missing catch bonds—we present a visionary roadmap.
Chao Yang +4 more
wiley +1 more source
, 2020 This is the first release of Hadamard Autoencoder based Social network prediction ...
gunjanmahindre
core +1 more source
Video Anomaly Detection Based on Convolutional Recurrent AutoEncoder
Sensors, 2022 As an essential task in computer vision, video anomaly detection technology is used in video surveillance, scene understanding, road traffic analysis and other fields.
Bokun Wang, Caiqian Yang
doaj +1 more source
Similarity‐Driven Framework for Efficient Polymer Property Prediction Under Data Scarcity Scenarios
Journal of Polymer Science, EarlyView.A new approach, based on structural and chemical similarities between polymers, is proposed to improve the performance of artificial neural networks in predicting the glass transition temperature under data‐scarce conditions. ABSTRACT Predicting polymer properties directly from chemical structure is essential for the rational design of advanced ...
Amaia Elizaran Mendarte +1 more
wiley +1 more source
Responsive Materials, EarlyView.Machine learning provides a unifying framework to connect structure, fluorescence properties, and applications of carbon‐based quantum dots. This review highlights how data‐driven strategies enable fluorescence regulation, reveal underlying mechanisms, and accelerate the rational design of functional carbon dots.
Liangfeng Chen +8 more
wiley +1 more source
Applied Sciences, 2023 Deep learning-based automatic modulation recognition networks are susceptible to adversarial attacks, posing significant performance vulnerabilities. In response, we introduce a defense framework enriched by tailored autoencoder (AE) techniques.
Chao Han +5 more
doaj +1 more source
Deterministic Switching‐Path Engineering of CMOS‐Integrated 2D Memristors for Neuromorphic Computing
Small, EarlyView.Deterministic grain‐boundary engineering in 2D MoTe2 defines resistive switching paths, while CMOS transistors impose gate‐tunable current compliance in a monolithically integrated 1T–1 M array. The resulting artificial synapses show stable, linear, and low‐variation analog weight updates, illustrating how materials‐level defect control can be ...
Jihoon Yang +12 more
wiley +1 more source
DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection
IEEJ Transactions on Electrical and Electronic Engineering, EarlyView.Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +1 more source
mappl-pldi24-ae/mappl-pldi24-ae: v0.1-beta
<h2>What's Changed</h2> <ul> <li>Add Docker Support by @mappl-pldi24-ae in https://github.com/mappl-pldi24-ae/mappl-pldi24-ae/pull/1</li> <li>Fix typos</li> </ul> <h2>New Contributors</h2> < ...
mappl-pldi24-ae
core +1 more source
Transformer-based autoencoder with ID constraint for unsupervised anomalous sound detection
EURASIP Journal on Audio, Speech, and Music Processing, 2023 Unsupervised anomalous sound detection (ASD) aims to detect unknown anomalous sounds of devices when only normal sound data is available. The autoencoder (AE) and self-supervised learning based methods are two mainstream methods.
Jian Guan +6 more
doaj +1 more source