MicroCloud Hologram Inc. Proposes Quantum AI Simulator Adopting Hybrid CPU-FPGA Method, Achieving Efficient Image Classification Simulation Through Heterogeneous Computing

MicroCloud Hologram Inc. (NASDAQ: HOLO), (“HOLO” or the "Company"), a technology service provider, proposed a quantum AI simulator that adopts a hybrid CPU-FPGA method. This system performs ...
BMJ

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China

Objective To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced ...
IEEE

Quo Vadis, Quantum Machine Learning?: Quantum kernel methods meet Earth observation

Abstract: The analysis of satellite images has attracted significant research interest due to its numerous applications and unparalleled scalability in Earth observation (EO). Although artificial ...
C&EN

A New Pulsed Neutron-Gamma Density Logging Method Based on Gamma-Ray Spectra and Machine Learning

However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...
Frontiers

Estimating rice yield-related traits using machine learning models integrating hyperspectral and texture features

Rapidly estimating multiple trait indicators simultaneously, nondestructively, and with high precision is an important means of accurate diagnosis in modern phenomics. Increasing the accuracy of ...
GitHub

Doubly-Robust-Kernel-Proxy-Variable-Algorithm

This repository provides code for a doubly robust algorithm for Proxy Causal Learning (PCL) using kernel methods, avoiding density ratio estimation. All code is written in Python 3 using the JAX ...
PNAS

Machine learning in chemistry

The Perspective by Tiwary et al. (8) offers a comprehensive overview of generative AI methods in computational chemistry. Approaches that generate new outputs (e.g., inferring phase transitions) by ...
Frontiers

The promise of quantum computing for population genetics and molecular ecology

Population geneticists increasingly confront a paradox: even with genome-scale datasets and advanced machine learning models, subtle population structure often remains undetected, particularly in ...
C&EN

A Machine Learning-Based Modeling Approach for Dye Removal Using Modified Natural Adsorbents

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. This study used machine learning models to investigate the potential of biosorbents ...
IEEE

Transfer Kernel Extreme Learning Machine Based on Bidirectional Cross Domain Approximation

Abstract: Kernel extreme learning machine (KELM) not only inherits the high learning efficiency of the traditional extreme learning machine (ELM), but also mitigates the instability caused by random ...