Results 161 to 170 of about 4,772,239 (326)

Autoencoders in Natural Language Processing: A Comprehensive Review

Computers
Autoencoder-based models have become a fundamental component of unsupervised and self-supervised learning in natural language processing (NLP), enabling models to learn compact latent representations through input reconstruction.
Moussa Redah, Wasfi G. Al-Khatib
doaj   +1 more source

Real‐Time Multicolor Fluorescence Microscopy via Cross‐Channel Acquisition and Deep‐Learning‐Based Inference

Advanced Intelligent Discovery, EarlyView.
Sequential multicolor fluorescence imaging in dynamic microsystems is constrained by acquisition speed and excitation dose. This study introduces a real‐time framework to reconstruct spectrally separated channels from reduced cross‐channel acquisitions (frames containing mixed spectral contributions).
Juan J. Huaroto, Yuxin Jin, Nicholas Roy, Sarthak Misra   +3 more
wiley   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

An Explainable AI Framework Integrating Variational Sparse Autoencoder and Random Forest for EEG-Based Epilepsy Detection

IEEE Access
Epilepsy is a medical condition characterized by sudden and frequent sensory disruptions which is commonly detected by electroencephalogram (EEG) analysis.
Pratiti Mishra, Himansu Das
doaj   +1 more source

Factorization Machine with Iterative Quantum Reverse Annealing: A Python Package for Batch Black‐Box Optimization With Reverse Quantum Annealing

Advanced Intelligent Discovery, EarlyView.
Factorization machine with iterative quantum reverse annealing (FMIRA) leverages quantum reverse annealing to perform batch black‐box optimization. Factorization machine with quantum annealing (FMQA) is a widely used python package for solving black‐box optimization problems using D‐Wave quantum annealers.
Andrejs Tučs, Ryo Tamura, Koji Tsuda
wiley   +1 more source

DeepMapper: Attention‐Based AutoEncoder for System Identification in Wound Healing and Stage Prediction

Advanced Intelligent Discovery, EarlyView.
The authors develop a deep learning model for real‐time tracking of wound progression. The deep learning framework maps the nonlinear evolution of a time series of images to a latent space, where they learn a linear representation of the dynamics. The linear model is interpretable and suitable for applications in feedback control.
Fan Lu, Ksenia Zlobina, Michael Briden, Oscar Avalos, Héctor Carrión, Sebastian Osorio, Hsin‐ya Yang, Alexandra Nava, Michelle D. Bagood, Marco Rolandi, Roslyn Rivkah Isseroff, Marcella Gomez   +11 more
wiley   +1 more source

Multi-Channel Multi-Scale Convolution Attention Variational Autoencoder (MCA-VAE): An Interpretable Anomaly Detection Algorithm Based on Variational Autoencoder

Sensors
With the rapid development of industry, the risks factories face are increasing. Therefore, the anomaly detection algorithms deployed in factories need to have high accuracy, and they need to be able to promptly discover and locate the specific equipment
Jingwen Liu, Yuchen Huang, Dizhi Wu, Yuchen Yang, Yanru Chen, Liangyin Chen, Yuanyuan Zhang   +6 more
doaj   +1 more source

An Autonomous Large Language Model‐Agent Framework for Transparent and Local Time Series Forecasting

Advanced Intelligent Discovery, EarlyView.
Architecture of the proposed large language model (LLM)‐based agent framework for autonomous time series forecasting in thermal power generation systems. The framework operates through a vertical pipeline initiated by natural language queries from users, which are processed by the LLM Agent Core powered by Llama.cpp and a ReAct loop with persistent ...
William Gouvêa Buratto, Gabriel Villarrubia Gonzalez, Ademir Nied, Laio Oriel Seman, Anne Carolina Rodrigues Klaar, Stefano Frizzo Stefenon   +5 more
wiley   +1 more source

Small sample pipeline DR defect detection based on smooth variational autoencoder and enhanced detection head faster RCNN [PDF]

The safe operation of gas pipelines is crucial for the safety of residents’ lives and property. However, accurately detecting defects within these gas pipelines is a challenging task. To improve the accuracy of defect detection in pipeline DR images with
You, Tianyang, Shi, Yanan, Zhang, Ting, Liu, Zhaoying, Rehman, Sadaqat Ur, Munshi, Amr   +5 more
core   +1 more source