Machine learning for condensed matter physics
E Bedolla, LC Padierna… - Journal of Physics …, 2020 - iopscience.iop.org
Condensed matter physics (CMP) seeks to understand the microscopic interactions of matter
at the quantum and atomistic levels, and describes how these interactions result in both …
at the quantum and atomistic levels, and describes how these interactions result in both …
Digitalization of the agro-food sector for achieving sustainable development goals: a review
A Sridhar, M Ponnuchamy, PS Kumar… - Sustainable Food …, 2023 - pubs.rsc.org
Food security and agricultural sustainability are essential for an equitable and healthy
society. Increasing food demand, growing inequalities, climate change and pandemics are …
society. Increasing food demand, growing inequalities, climate change and pandemics are …
Clustering by fast search and find of density peaks
A Rodriguez, A Laio - science, 2014 - science.org
Cluster analysis is aimed at classifying elements into categories on the basis of their
similarity. Its applications range from astronomy to bioinformatics, bibliometrics, and pattern …
similarity. Its applications range from astronomy to bioinformatics, bibliometrics, and pattern …
SOD‐YOLO: a small target defect detection algorithm for wind turbine blades based on improved YOLOv5
R Zhang, C Wen - Advanced Theory and Simulations, 2022 - Wiley Online Library
Early and effective detection of wind turbine blade (WTB) surface defects can avoid complex
and expensive repair problems and serious safety hazards. The traditional target detection …
and expensive repair problems and serious safety hazards. The traditional target detection …
iPhos‐PseEvo: identifying human phosphorylated proteins by incorporating evolutionary information into general PseAAC via grey system theory
Protein phosphorylation plays a critical role in human body by altering the structural
conformation of a protein, causing it to become activated/deactivated, or functional …
conformation of a protein, causing it to become activated/deactivated, or functional …
[PDF][PDF] A survey on unsupervised machine learning algorithms for automation, classification and maintenance
The paper is comprehensive survey of methodologies and techniques used for
Unsupervised Machine Learning that are used for learn complex, highly non-linear models …
Unsupervised Machine Learning that are used for learn complex, highly non-linear models …
Systems metabolic engineering meets machine learning: a new era for data‐driven metabolic engineering
KV Presnell, HS Alper - Biotechnology journal, 2019 - Wiley Online Library
The recent increase in high‐throughput capacity of 'omics datasets combined with advances
and interest in machine learning (ML) have created great opportunities for systems …
and interest in machine learning (ML) have created great opportunities for systems …
A transfer learning approach for improved classification of carbon nanomaterials from TEM images
The extensive use of carbon nanomaterials such as carbon nanotubes/nanofibers
(CNTs/CNFs) in industrial settings has raised concerns over the potential health risks …
(CNTs/CNFs) in industrial settings has raised concerns over the potential health risks …
Using large datasets to understand nanotechnology
K Paunovska, D Loughrey, CD Sago… - Advanced …, 2019 - Wiley Online Library
Advances in sequencing technologies have made studying biological processes with
genomics, transcriptomics, and proteomics commonplace. As a result, this suite of …
genomics, transcriptomics, and proteomics commonplace. As a result, this suite of …
Thickness determination of ultrathin 2D materials empowered by machine learning algorithms
Y Mao, L Wang, C Chen, Z Yang… - Laser & Photonics …, 2023 - Wiley Online Library
The number of layers of 2D materials is of great significance for regulating the performance
of nanoelectronic devices and optoelectronic devices, where the optimal thickness of the …
of nanoelectronic devices and optoelectronic devices, where the optimal thickness of the …