A scalable and accurate tool to characterize entanglement in quantum processors

Quantum computers, computing systems that process information leveraging quantum mechanical effects, could soon outperform ...
IEEE

Combination Manner of Sampling Method and Model Structure: The Key Factor for Rice Mapping Based on Sentinel-1 Images Using Data-Driven Machine Learning

Abstract: Agricultural remote sensing community is increasingly focusing on enhancing crop mapping accuracy by improving data-driven machine-learning model structures, yet ignoring impact of ...
C&EN

Machine-Learning Potential Molecular Dynamics Reveals the Critical Role of Flexibility in Solid–Liquid Nanofluidic Friction

Shanghai Key Laboratory of Mechanics in Energy Engineering, Shanghai Institute of Applied Mathematics and Mechanics, School of Mechanics and Engineering Science, Shanghai University, Shanghai 200444, ...
Phys.org

Deep learning method enables efficient Boltzmann distribution sampling across a continuous temperature range

A research team has developed a novel direct sampling method based on deep generative models. Their method enables efficient sampling of the Boltzmann distribution across a continuous temperature ...
IEEE

Human Activity Recognition in Smart Homes Using IMU Wristbands: A Comparative Study of Sampling Strategies and Machine Learning Models

Abstract: This research explores Human Activity Recognition (HAR) for monitoring activities in smart homes using IMU wristbands, specific sampling strategies, and machine learning models to enhance ...
Nature

Machine-learning model generates images using light

Machine-learning models identify relationships in a data set (called the training data set) and use this training to perform operations on data that the model has not encountered before. This could ...