Results 151 to 160 of about 13,735 (297)

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

A Perceived Environment Design using a Multi-Modal Variational Autoencoder for learning Active-Sensing [PDF]

, 2019
Korthals T, Schilling M, Leitner J. A Perceived Environment Design using a Multi-Modal Variational Autoencoder for learning Active-Sensing. 2019.This contribution comprises the interplay between a multi-modal variational autoencoder and an environment ...
Schilling, Malte ; https://orcid.org/, Leitner, Jürgen, Korthals, Timo ; https://orcid.org/   +2 more
core  

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

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

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Identifying Tampered Radio-Frequency Transmissions in LoRa Networks Using Machine Learning

Sensors
Long-range networks, renowned for their long-range, low-power communication capabilities, form the backbone of many Internet of Things systems, enabling efficient and reliable data transmission.
Nurettin Selcuk Senol, Amar Rasheed, Mohamed Baza, Maazen Alsabaan   +3 more
doaj   +1 more source

A Robust Deep Temporal Causal Discovery Platform for Single‐Cell Gene Regulatory Network Reconstruction

Advanced Intelligent Discovery, EarlyView.
scTIGER2.0 is a deep‐learning framework that infers gene regulatory networks from single‐cell RNA sequencing data. By integrating correlation, pseudotime ordering, deep learning and bootstrap‐based significance testing, it reduces false positives and reveals directional gene interactions.
Nishi Gupta, Madison Dautle, Shaoqiang Zhang, Yong Chen   +3 more
wiley   +1 more source