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https://doi.org/10.2139/ssrn.4646605

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inferredcites →https://doi.org/10.1002/pssb.201248051openalex-extracted
The correlation between the electron work function and yield strength of metals
inferredcites →https://doi.org/10.1016/j.actamat.2014.04.033openalex-extracted
Electronic and thermodynamic criteria for the occurrence of high entropy alloys in metallic systems
inferredcites →https://doi.org/10.1016/j.actamat.2015.01.051openalex-extracted
The electronic origin of strengthening and ductilizing magnesium by solid solutes
inferredcites →https://doi.org/10.1016/j.actamat.2019.03.010openalex-extracted
Machine learning assisted design of high entropy alloys with desired property
inferredcites →https://doi.org/10.1016/j.actamat.2021.117431openalex-extracted
A machine learning-based alloy design system to facilitate the rational design of high entropy alloys with enhanced hardness
inferredcites →https://doi.org/10.1016/j.actamat.2022.117924openalex-extracted
Efficient machine-learning model for fast assessment of elastic properties of high-entropy alloys
inferredcites →https://doi.org/10.1016/j.actamat.2023.119177openalex-extracted
Rapid Discovery of High Hardness Multi Principal Element Alloys Using a Generative Adversarial Network Model
inferredcites →https://doi.org/10.1016/j.commatsci.2021.110647openalex-extracted
Learning phase selection and assemblages in High-Entropy Alloys through a stochastic ensemble-averaging model
inferredcites →https://doi.org/10.1016/j.cosrev.2021.100378openalex-extracted
Conceptual and empirical comparison of dimensionality reduction algorithms (PCA, KPCA, LDA, MDS, SVD, LLE, ISOMAP, LE, ICA, t-SNE)
inferredcites →https://doi.org/10.1016/j.cpc.2022.108398openalex-extracted
HEAPS: A user-friendly tool for the design and exploration of high-entropy alloys based on semi-empirical parameters
inferredcites →https://doi.org/10.1016/j.eswa.2021.115020openalex-extracted
Explaining dimensionality reduction results using Shapley values
inferredcites →https://doi.org/10.1016/j.heliyon.2021.e06199openalex-extracted
pyDRMetrics - A Python toolkit for dimensionality reduction quality assessment
inferredcites →https://doi.org/10.1016/j.jallcom.2017.12.065openalex-extracted
An electron work function based mechanism for solid solution hardening
inferredcites →https://doi.org/10.1016/j.jallcom.2020.153766openalex-extracted
Microstructure exploration and an artificial neural network approach for hardness prediction in AlCrFeMnNiWx High-Entropy Alloys
inferredcites →https://doi.org/10.1016/j.jallcom.2023.169329openalex-extracted
Interpretable hardness prediction of high-entropy alloys through ensemble learning
inferredcites →https://doi.org/10.1016/j.jmrt.2022.12.143openalex-extracted
Predict the phase formation of high-entropy alloys by compositions
inferredcites →https://doi.org/10.1016/j.jmst.2017.07.013openalex-extracted
Effect of lattice distortion on solid solution strengthening of BCC high-entropy alloys
inferredcites →https://doi.org/10.1016/j.jmst.2021.01.054openalex-extracted
Machine learning of phases and mechanical properties in complex concentrated alloys
inferredcites →https://doi.org/10.1016/j.jmst.2022.07.059openalex-extracted
Predicting single-phase solid solutions in as-sputtered high entropy alloys: High-throughput screening with machine-learning model
inferredcites →https://doi.org/10.1016/j.mser.2021.100645openalex-extracted
Machine-learning and high-throughput studies for high-entropy materials
inferredcites →https://doi.org/10.1016/j.neucom.2022.05.119openalex-extracted
Enhance explainability of manifold learning
inferredcites →https://doi.org/10.1016/j.scriptamat.2020.04.016openalex-extracted
Machine Learned Feature Identification for Predicting Phase and Young's Modulus of Low-, Medium- and High-Entropy Alloys
inferredcites →https://doi.org/10.1038/s41524-017-0024-0openalex-extracted
Atomic and electronic basis for the serrations of refractory high-entropy alloys
inferredcites →https://doi.org/10.1038/s41597-020-00768-9openalex-extracted
Expanded dataset of mechanical properties and observed phases of multi-principal element alloys
inferredcites →https://doi.org/10.1063/1.3614475openalex-extracted
Generic relation between the electron work function and Young's modulus of metals
inferredcites →https://doi.org/10.1086/450136openalex-extracted
Regional Inequality and the Process of National Development: A Description of the Patterns
inferredcites →https://doi.org/10.1109/tkde.2022.3169333openalex-extracted
Stable Prediction with Leveraging Seed Variable
inferredcites →https://doi.org/10.1179/1743284715y.0000000018openalex-extracted
Phase selection rules for cast high entropy alloys: An overview
inferredcites →https://doi.org/10.21105/joss.00861openalex-extracted
UMAP: Uniform Manifold Approximation and Projection
inferredcites →https://doi.org/10.2139/ssrn.4266764openalex-extracted
Rapid Discovery of High Hardness Multi Principal Element Alloys Using a Generative Adversarial Network Model
inferredcites →https://doi.org/10.2307/2223525openalex-extracted
The Measurement of the Inequality of Incomes
inferredcites →https://doi.org/10.3166/acsm.31.633-648openalex-extracted
Recent progress in high-entropy alloys
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-extracted
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.48550/arxiv.2210.13597openalex-extracted
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