M. Costa

Materials Chemistry · with Acosta · 2019

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

Subfields

• Materials Chemistry — 164 citations into it

Whom M. Costa trusts

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

1. J. Behler (in Materials Chemistry)

Papers from M. Costa's perspective

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

1. I and J
2. The Elements of Statistical Learning
3. Self-Consistent Equations Including Exchange and Correlation Effects
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Deep Learning
6. Inhomogeneous Electron Gas
7. Gradient-based learning applied to document recognition
8. Generalized Gradient Approximation Made Simple.
9. Generalized neural-network representation of high-dimensional potential-energy surfaces.
10. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)

Their papers

• From DFT to machine learning: recent approaches to materials science–a review (2019) — 781 citations