Ming Hu

Materials Chemistry · with Cui · 2020

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Materials Chemistry — 15 citations into it

Whom Ming Hu trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Logan T. Ward

Papers from Ming Hu's perspective

Ordered by how strongly the researchers Ming Hu trusts endorse each paper. Same corpus, a different order for every researcher.

1. A General-Purpose Machine Learning Framework for Predicting Properties of Inorganic Materials
2. Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations
3. ElemNet: Deep Learning the Chemistry of Materials From Only Elemental Composition (Scientific Reports)
4. Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties.
5. Scikit-learn: Machine Learning in Python
6. AFLOWLIB.ORG: A distributed materials properties repository from high-throughput ab initio calculations
7. Materials Design and Discovery with High-Throughput Density Functional Theory: The Open Quantum Materials Database (OQMD)
8. Matminer: An open source toolkit for materials data mining (Computational materials science)
9. Distilling Free-Form Natural Laws from Experimental Data
10. Extrapolation and learning equations

Their papers

• Evaluating explorative prediction power of machine learning algorithms for materials discovery using k-fold forward cross-validation (2020) — 300 citations