Tech Xplore

Mistaken correlations: Why it's critical to move beyond overly aggregated machine-learning metrics

MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...
GitHub

time-series-analysis

💧 Forecast river discharge using machine learning with optimized ensemble models for accurate next-day predictions and flexible time series applications.
IEEE

HITS: Hierarchical Interpretable Time Series Classification via Multiple Instance Learning

Abstract: Interpretability in multivariate time series classification (MTSC) remains a fundamental challenge, as state-of-the-art deep learning models often operate as "black boxes" due to their ...
Live Science

Scientists use quantum machine learning to create semiconductors for the first time – and it could transform how chips are made

Researchers have found a way to make the chip design and manufacturing process much easier — by tapping into a hybrid blend of artificial intelligence and quantum computing. When you purchase through ...
Scientific Research Publishing

An Evaluation of Machine Learning Models for Threat Classification in IoT Devices ()

1 Center for Cyberspace Studies, Nasarawa State University, Keffi, Nigeria. 2 Department of Computer Engineering, Nile University of Nigeria, Abuja, Nigeria. 3 Department of Public and International ...
Frontiers

Classification of neurodegenerative diseases using brain effective connectivity and machine learning techniques: a systematic review

Department of Preventive Medicine, College of Basic Medicine and Forensic Medicine, Henan University of Science and Technology, Luoyang, China Background: Effective connectivity (EC) refers to the ...
Frontiers

Migraine triggers, phases, and classification using machine learning models

1 San Juan Bautista School of Medicine, Caguas, Puerto Rico, United States 2 Independent Researcher, Monmouth County, NJ, United States Background: In many countries, patients with headache disorders ...
IEEE

Hybrid Quantum ResNet for Time Series Classification

Abstract: Residual networks (ResNet) are known to be effective for image classification. However, challenges such as computational time remain because of the significant number of parameters. Quantum ...