Tech Xplore

Interrupting encoder training in diffusion models enables more efficient generative AI

A new framework for generative diffusion models was developed by researchers at Science Tokyo, significantly improving ...
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 ...
Live Science

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

Quantum machine learning is a hybrid approach that combines classical data with quantum computing methods. In classical computing, data is stored in bits encoded as a 0 or 1. Quantum computers use ...
IEEE

Energy-Efficient Federated Learning in Symbiotic IoT Networks through Heterogeneity-aware Client Sampling

Abstract: Federated Learning (FL) in symbiotic IoT networks is a promising collaborative paradigm that utilizes IoT devices to co-train machine learning models, promising to accelerate edge ...
Scientific Research Publishing

Huang, A. A., & Huang, S. Y. (2023). Increasing Transparency in Machine Learning through Bootstrap Simulation and Shapely Additive Explanations. PLOS ONE, 18, e0281922.

ABSTRACT: Machine learning (ML) has revolutionized risk management by enabling organizations to make data-driven decisions with higher accuracy and speed. However, as machine learning models grow more ...
Frontiers

Advances in machine learning for the detection and characterization of microplastics in the environment

1 Department of Environmental Sciences, Jahangirnagar University, Dhaka, Bangladesh 2 Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, Sweden ...
C&EN

Improved Machine Learning Predictions of EC50s Using Uncertainty Estimation from Dose–Response Data

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In early-stage drug design, machine learning models often rely on compressed ...
Frontiers

Early prediction of sepsis associated encephalopathy in elderly ICU patients using machine learning models: a retrospective study based on the MIMIC-IV database

Background: Sepsis associated encephalopathy (SAE) is prevalent among elderly patients in the ICU and significantly affects patient prognosis. Due to the symptom similarity with other neurological ...